Oma Academic Writer

Academic Writer: Publication-Grade English Prose Specialist

Scheduling

Goal

Produce, revise, and audit publication-grade academic English prose so that every output simultaneously satisfies the Sentence Structure Protocol, Verb Protocol, Hedging Protocol, and Anti-AI Compliance Checklist, with every claim mapped to verifiable evidence.

Intent signature

• "draft this essay / report / executive summary / conclusion / literature review"
• "rewrite this paragraph in academic English"
• "polish this draft to top-band quality" / "revise to match the rubric"
• "run an anti-AI audit on this prose"
• "check sentence structure variety" / "fix monotonous rhythm"
• "the prose sounds AI-generated, make it pass"
• "verify claims against evidence" / "reverse outline this section"

When to use

• Drafting or revising academic reports, essays, or analysis sections
• Writing executive summaries, conclusions, or literature reviews
• Rewriting AI-sounding prose into natural academic English
• Polishing draft text to achieve top-band rubric quality (HD, A, top-band, etc.)
• Reviewing prose for sentence variety, verb quality, hedging, and anti-AI compliance
• Any task requiring formal academic English output bound by a rubric

When NOT to use

• Translation tasks → use oma-translator
• Source discovery, citation gathering, or scholarly literature search → use oma-scholar
• Rubric / assignment-spec parsing and task decomposition → use oma-pm
• Code documentation, README, or API reference text → use the relevant domain skill (oma-frontend, oma-backend, oma-mobile, oma-db, etc.)
• Informal communication, chat, or marketing copy → no skill needed
• Non-English academic writing → call oma-translator for the target language after drafting in English

Expected inputs

• mode: one of draft | revise | review
• rubric_or_constraint: assignment brief, rubric file, or word/structure limits (path or inline text)
• existing_draft: prior text to revise or audit (path or inline text); required for revise and review
• source_data: available evidence, figures, citations the writer may use
• target_register: defaults to formal academic English

Expected outputs

• draft mode: section heading + drafted prose + Writing Notes (sentence mix, key verbs, anti-AI flags resolved, paragraph lengths) + Claim-Evidence Map
• revise mode: original block, revised block, list of specific changes (verb upgrades, structure variation, anti-AI fixes)
• review mode: PASS/FAIL Compliance Report across Sentence Structure, Verb Quality, Anti-AI, Specificity, Hedging, Paragraph Clarity, Rhythm/Burstiness, Claim-Evidence Alignment, plus recommended fixes

Dependencies

• resources/anti-ai-checklist.md: banned vocabulary, banned structural patterns, sentence-level checks
• resources/sentence-structure-reference.md: four sentence types, length targets, common errors
• resources/academic-verb-tiers.md: banned generic verbs and tiered academic-corpus replacements
• resources/hedging-guide.md: calibrated certainty expressions matched to evidence strength
• ../_shared/core/context-loading.md: task-relevant resource loading
• ../_shared/core/quality-principles.md: shared quality bar

Control-flow features

• Mode branching: draft vs revise vs review produce different output formats and pass sequences
• Rubric-quote gate: refuses to apply a rule until the literal constraint text is quoted from the source
• Citation gap branch: when a claim lacks evidence, weaken or remove rather than fabricate; optionally hand off to oma-scholar
• Language branch: non-English target hands off to oma-translator after the English pass
• Iterative AUDIT: every fix loops back through the anti-AI checklist before emit

Structural Flow

Entry

1. Identify the mode (draft, revise, review) and the rubric source. 2. Quote the exact constraint text (word limits, structural requirements, mandatory sections, rubric rows) before applying any rule. 3. If revising or reviewing, read the existing draft in full first; if drafting, confirm available source data and citations. 4. Index resources/ and pre-select the verb tier and sentence mix targets for the section.

Scenes

1. PREPARE: load rubric, existing draft, source data; record quoted constraints; pick sentence mix and 2–3 anchor verbs per paragraph. 2. ACQUIRE: read resources/sentence-structure-reference.md, academic-verb-tiers.md, and hedging-guide.md only for the patterns relevant to the current section. 3. ACT: write or revise prose with the four protocols enforced simultaneously: Sentence Structure (4 types, varied length, varied openers), Verb (no banned generic verbs as main verbs; prefer tier-1/2 academic verbs), Hedging (match strength to evidence), and Topic-Support-Conclude paragraphing. 4. VERIFY: audit against resources/anti-ai-checklist.md (vocabulary clusters, structural patterns, sentence-level checks); apply reverse outlining and build the Claim-Evidence Map; weaken or remove unsupported claims. 5. FINALIZE: read-aloud test, cohesion check, specificity audit, word-count verification, paragraph-length variation, rhythm check; emit per the mode's output format.

Transitions

• If a rubric line is ambiguous → quote it back to the user and ask for interpretation; do not infer combined rules.
• If a claim cannot be supported by available evidence → weaken with hedging or remove; if a citation gap is structural, NOTIFY oma-scholar.
• If the target language is non-English → finish the English pass, then hand off to oma-translator.
• If the same anti-AI flag survives one fix attempt → restructure the surrounding two sentences instead of word-substitution alone.
• If an output mode mismatch is detected (e.g., user asked for review but supplied a fresh prompt) → confirm the mode before producing output.

Failure and recovery

Exit

• Success: every protocol PASSes, the Claim-Evidence Map has no unsupported entries, word count complies, and the mode-specific output format is fully populated.
• Partial success: emit prose with explicit needs evidence / pending citation markers and report which protocol items remain at risk; flag handoff candidates.
• Failure: refuse to emit and report the blocking ambiguity (rubric quote missing, source data absent, contradictory constraints).

Logical Operations

Actions

Tools and instruments

• Read / Edit / Write for draft and rubric files
• resources/anti-ai-checklist.md, sentence-structure-reference.md, academic-verb-tiers.md, hedging-guide.md
• Topic-Support-Conclude paragraph template (inline)
• Claim-Evidence Map (inline 3-column table: Claim / Evidence / Status)
• Output-format blocks per mode (Draft / Revision / Review)

Canonical workflow path

1. READ rubric/draft and quote the exact literal constraint text; pin word limits, mandatory sections, and rubric rows. 2. PLAN each paragraph as Topic-Support-Conclude; pre-select the sentence-type mix and 2–3 anchor verbs from academic-verb-tiers.md. 3. DRAFT prose with Sentence Structure, Verb, Hedging, and Topic-Support-Conclude protocols enforced simultaneously. 4. AUDIT the draft against resources/anti-ai-checklist.md (banned vocabulary clusters, banned structural patterns, sentence-level checks) and fix every flag. 5. REVERSE-OUTLINE the section and build the Claim-Evidence Map; weaken or remove any unsupported claim. 6. POLISH with read-aloud, cohesion, specificity, word-count, rhythm, and paragraph-length-variation checks; emit in the mode's output format.

Resource scope

Preconditions

• A rubric / constraint or an existing draft (or both) is provided.
• The target register is academic English. If the final deliverable is non-English, the user has agreed to a downstream oma-translator handoff.
• The source data needed to support claims is available, or unsupported claims are explicitly allowed to be weakened or removed.

Effects and side effects

• Writes drafted, revised, or reviewed prose to the user's working location (file or inline).
• Does not modify resources/ reference files.
• Does not fetch external citations; defers to oma-scholar when discovery is required.
• May NOTIFY adjacent skills but does not auto-spawn them; user or workflow drives the actual handoff.

Guardrails

1. Every sentence must be verifiable; never fabricate data, statistics, or citations. 2. Quote-before-judgment: cite the literal constraint or rubric text before applying any rule. 3. Never combine distinct rules to invent a new constraint; apply rules exactly as written. 4. Banned generic verbs (show, have, make, do, get, use, give, say, put, see, come, go, take, find, know, think, want, try, need, seem, become, keep, help, start, turn, bring, run, hold, set) must not appear as main verbs; replace per academic-verb-tiers.md. 5. Never place 3+ sentences of the same structural type consecutively; vary length (short 8–15, medium 16–25, long 26–40 words) and openers. 6. Match hedge strength to evidence strength per hedging-guide.md; never use absolute claim words (definitely, clearly, obviously) outside mathematical facts; never first-person I think / I believe. 7. Never cluster 3+ flagged AI-vocabulary items in a single paragraph; never insert promotional or inflated language; never append superficial -ing clauses for analysis. 8. Em dashes ≤ 1 per paragraph; semicolons ≤ 2 per 1000 words; sentence-case headers; no didactic disclaimers (It is important to note) or summary phrases (In summary, Overall). 9. Every claim must map to evidence in the Claim-Evidence Map; weaken or remove unsupported claims rather than emit them. 10. Read aloud before emit; if a sentence does not flow naturally, restructure it.

References

• Anti-AI checklist: resources/anti-ai-checklist.md
• Sentence-structure reference: resources/sentence-structure-reference.md
• Academic verb tiers: resources/academic-verb-tiers.md
• Hedging guide: resources/hedging-guide.md
• Shared context loading: ../_shared/core/context-loading.md
• Shared quality principles: ../_shared/core/quality-principles.md

Academic verb tiers

Ranked by frequency in a corpus of academic papers. Higher tiers are more universally appropriate; lower tiers are more specialised.

Source: top 437 verbs from an academic corpus (frequency-ranked).

Banned verbs (generic / low-level)

These verbs lack precision and register in academic writing. Never use them as the main verb of a sentence.

Tier 1: universal academic verbs (frequency rank 1–30)

These are safe in any academic context. Use liberally.

Tier 2: strong academic verbs (frequency rank 31–80)

Excellent for adding precision and variety.

Tier 3: precision verbs (frequency rank 81–200)

For nuanced, specific claims. Excellent for adding sophistication without over-reaching.

Verb selection by rhetorical purpose

Usage notes

1. Tier 1 verbs are always safe; use these as your default vocabulary 2. Tier 2 verbs add precision; use 3–5 per paragraph for variety 3. Tier 3 verbs add sophistication; use 1–2 per paragraph to avoid overly dense prose 4. Borderline AI words (leverage, enhance, highlight, showcase): limit to 1 per page maximum; prefer alternatives 5. Match verb to evidence strength: "demonstrate" > "suggest" > "may indicate" in confidence 6. Prefer single verbs over phrasal verbs: "investigate" not "look into", "improve" not "make better"

Anti-AI Writing Checklist for Academic English

Academic prose must read as authentically human-written. This checklist targets patterns that AI detection tools and experienced markers identify as machine-generated.

Pre-submission Scan

Run through each category. A single FAIL requires revision before output.

1. Vocabulary Clustering

Rule: No more than 2 of the following words in any single paragraph.

Flagged Words (High AI Correlation)

Additionally, align with, crucial, delve, emphasize/emphasizing, enduring, enhance, foster/fostering, garner, highlight (as verb), interplay, intricate/intricacies, key (as adjective), landscape (abstract), multifaceted, nuanced, pivotal, robust, seamless, showcase, synergy, tapestry (abstract), testament, underscore (as verb), valuable, vibrant, holistic, paradigm, cutting-edge, groundbreaking, comprehensive, Furthermore, Moreover, navigating, realm, embark, noteworthy

Self-check

• [ ] Count flagged words per paragraph
• [ ] If 3+ found → replace with plain academic alternatives
• [ ] Check entire document for repeated use of the same flagged word

2. Inflated Significance

Rule: Never inflate the importance of a subject beyond what the evidence supports.

Banned Phrases

Self-check

• [ ] Does every significance claim have supporting evidence cited?
• [ ] Is the language proportional to the evidence?
• [ ] Would a sceptical reader accept the level of emphasis?

3. Superficial -ing Analysis

Rule: Never append a present participle clause as shallow analysis.

Pattern to Detect

"[Statement], highlighting/ensuring/reflecting/contributing to/fostering [vague significance]."

Fix

• If the -ing clause adds genuine meaning → promote it to a full sentence with evidence
• If it adds no meaning → delete it entirely

Self-check

• [ ] Search for -ing clauses at end of sentences
• [ ] For each: does it add substantive analysis or just filler?
• [ ] Rewrite or delete accordingly

4. Copula Avoidance

Rule: Use "is/are/has" when they are the natural choice. Do not replace them with fancier alternatives.

Pattern to Detect

Self-check

• [ ] Scan for "serves as", "stands as", "marks", "represents" used as copula substitutes
• [ ] Replace with "is/are" unless the verb genuinely adds meaning

5. Structural Patterns

Negative Parallelisms

• Avoid: "Not only X but also Y", "It's not just about X, it's about Y"
• Fix: State both facts directly without the parallelism

Rule of Three

• Avoid: "adjective, adjective, and adjective" for shallow coverage
• Fix: Reduce to two descriptors, or expand each into substantive analysis

Elegant Variation (Synonym Cycling)

• Avoid: Rotating terms for the same concept (students → learners → participants)
• Fix: Pick one term and use it consistently throughout

False Ranges

• Avoid: "from X to Y" with unrelated or vaguely connected endpoints
• Fix: Drop the construction or specify a meaningful scale

Self-check

• [ ] No negative parallelisms used for rhetorical effect alone
• [ ] No triple adjective/noun lists without substantive expansion
• [ ] Terminology is consistent (no synonym cycling)
• [ ] All "from X to Y" constructions have a meaningful scale

6. Formatting Artefacts

Boldface

• Do not bold terms mechanically in lists ("Term: description")
• Bold only for genuine emphasis in running prose

Em Dashes

• Limit to 1 per paragraph maximum
• Prefer commas or parentheses
• Never use em dashes for emphasis that a natural sentence structure can deliver

Colons

• Prefer natural sentence flow over colon constructions. Subordination (because, although, while) and coordination (and, but, so) almost always produce more readable prose than a colon.
• Colons are acceptable only for:
• Formal definitions: "Normalization is defined as: ..."
• Introducing block quotations
• Ratios or time stamps (e.g., 2:1, 14:30)
• Avoid colons that introduce inline lists, elaborations, or explanations mid-sentence.
• Bad: "The study examined three factors: temperature, humidity, and wind speed."
• Good: "The study examined temperature, humidity, and wind speed."
• Also good: "The study examined three factors, namely temperature, humidity, and wind speed."
• Avoid the "Label: description" pattern in running prose (this is a list/slide-deck pattern, not academic prose).

Title Case

• Use sentence case for all section headings
• Exception: proper nouns

Tables

• Do not present information as a table when prose is more appropriate
• Tables for quantitative comparison or reference data only

Self-check

• [ ] No mechanical bold patterns
• [ ] Em dashes used sparingly (≤1 per paragraph)
• [ ] Colons used only for formal definitions, block quotations, or ratios
• [ ] All headings in sentence case
• [ ] Tables justified for the content type

7. Meta-commentary

Banned Phrases

Self-check

• [ ] No meta-commentary phrases found
• [ ] Transitions use content-based links, not meta-phrases

8. Sentence Openers

Rule: Vary how sentences begin

Avoid starting 3+ consecutive sentences with:

• The same word (especially "The", "This", "It", "However")
• Subject-verb pattern every time

Vary with:

• Adverbial phrases: "Between 2015 and 2020, ..."
• Prepositional phrases: "In the context of ..."
• Participial phrases: "Drawing on longitudinal data, ..."
• Dependent clauses: "Although the sample size was limited, ..."
• Transitional phrases (non-AI): "By contrast, ...", "More specifically, ...", "In parallel, ..."

Self-check

• [ ] No 3+ consecutive sentences starting the same way
• [ ] At least 3 different opener types per paragraph

9. Rhythm & Paragraph Length

Rule: AI-generated text exhibits characteristically uniform sentence length and paragraph blocks. Natural academic writing has variation.

Sentence rhythm (burstiness)

• If 5+ consecutive sentences all fall within the same narrow word-count range (e.g., all 20–25 words), flag for revision
• Insert a short sentence (≤10 words) to break metronomic patterns
• Combine two short sentences into one complex one if the pattern is monotonously short
• Read the paragraph aloud; if it feels metronomic, vary it

Paragraph length variation

• Vary paragraph length naturally: 2–8 sentences per paragraph
• Uniform 4–5 sentence paragraphs signal AI; avoid this pattern
• Short paragraphs (2–3 sentences) create emphasis
• Longer paragraphs (6–8 sentences) develop complex arguments
• Never have 4+ consecutive paragraphs of the same length (±1 sentence)

Semicolons

• Limit: ≤2 per 1000 words
• AI text chains independent clauses with semicolons where a period would be clearer
• Reserve semicolons for closely related parallel structures

Self-check

• [ ] No 5+ consecutive sentences in the same word-count range
• [ ] Paragraph lengths vary (no 4+ consecutive same-length paragraphs)
• [ ] Semicolons ≤2 per 1000 words

10. Chatbot Artefacts

Never Include

• "I hope this helps"
• "Let me know if you need anything else"
• "Here is a breakdown of..."
• "Of course!", "Certainly!"
• "As an AI language model"
• Subject lines ("Subject: ...")
• Knowledge-cutoff disclaimers

Self-check

• [ ] Zero chatbot artefacts in output

Final Verification

Run all checks in sequence:

1. [ ] Vocabulary clustering: no 3+ flagged words per paragraph 2. [ ] Inflated significance: proportional to evidence 3. [ ] No superficial -ing analysis 4. [ ] Natural copula usage: "is/are" used where appropriate 5. [ ] No banned structural patterns 6. [ ] Clean formatting: no artefacts (bold, em dash, colon, tables) 7. [ ] No meta-commentary 8. [ ] Varied sentence openers 9. [ ] Rhythm & paragraph length: no metronomic patterns or uniform blocks 10. [ ] Zero chatbot artefacts 11. [ ] Natural sentence flow: colons and em dashes not substituting for proper subordination/coordination 12. [ ] Claim-evidence alignment: every major claim has cited support

Result: PASS only if all 12 checks clear.

Hedging guide for academic English

Academic writing requires calibrated certainty: neither overclaiming nor excessive caution.

Evidence-to-hedge mapping

Hedging devices

Modal verbs (ordered by certainty)

Hedging verbs

Hedging adverbs

Hedging nouns

possibility, tendency, likelihood, indication, suggestion, assumption, interpretation, speculation

Hedging prepositional phrases

according to, on the basis of, in light of, given the limitations of, with reference to, from the perspective of

Rules

1. Match hedge to evidence

Every claim in academic writing must carry the appropriate degree of certainty.

Strong evidence → assertive language:

"The regression analysis demonstrates a statistically significant correlation (p < .001) between match duration and surface type."

Moderate evidence → moderate hedge:

"The findings suggest that match duration tends to increase on clay surfaces."

Limited evidence → strong hedge:

"Preliminary data may indicate a relationship between surface type and match duration, although further investigation is warranted."

2. Never over-hedge strong evidence

If the data clearly support a claim, do not weaken it with unnecessary hedges.

• Bad: "The data might possibly seem to suggest that the correlation could potentially exist."
• Good: "The data demonstrate a strong correlation."

3. Never under-hedge weak evidence

If the evidence is limited, do not present claims as established fact.

• Bad: "Surface type determines match duration." (stated as fact from limited data)
• Good: "Surface type appears to influence match duration."

4. Avoid double hedging

Using two hedge devices where one suffices weakens the claim unnecessarily.

• Bad: "It might possibly be the case that..."
• Good: "It may be the case that..."

• Bad: "The results seem to suggest that..."
• Good: "The results suggest that..." or "The results seem to indicate that..."

5. Use attribution hedging for interpretive claims

When offering your own analysis (not reporting others' findings), attribute the interpretation explicitly.

• "This pattern appears to reflect broader changes in playing strategy."
• "One interpretation of this trend is that..."
• "Based on this analysis, it is reasonable to infer that..."

6. Avoid "I think" / "I believe"

These are too informal for academic writing. Replace with:

7. Never use "clearly/obviously/definitely" unless justified

These intensifiers are appropriate only for:

• Mathematical certainties: "The mean is clearly higher than the median."
• Logical necessities: "If A > B and B > C, then A is definitively greater than C."
• Universally accepted facts: appropriate in very limited contexts

For all other claims, remove the intensifier and let the evidence speak.

Quick reference: hedge calibration checklist

Before submitting any academic text:

• [ ] Does every claim carry appropriate hedging for its evidence base?
• [ ] No double-hedging found?
• [ ] No "clearly/obviously" used without mathematical or logical justification?
• [ ] No "I think/believe" constructions?
• [ ] Interpretive claims attributed with "appears to", "one interpretation", etc.?
• [ ] Strong evidence not weakened by unnecessary hedges?
• [ ] Weak evidence not presented as established fact?

Sentence structure reference for academic English

Four sentence types

1. Simple sentence

One independent clause in a subject-verb pattern.

Use for: High-impact statements, clear assertions, topic sentences.

Examples:

• The Australian government introduced an official carbon tax on 1 July 2012.
• This dataset contains 120 years of match records.
• Performance declined sharply after the 2018 rule changes.

Target: 20–30% of sentences per paragraph.

2. Compound sentence

Two independent clauses connected by a coordinating conjunction (FANBOYS: for, and, nor, but, or, yet, so).

Use for: Balanced comparisons, contrasts, cause-effect pairs.

Examples:

• The Australian government introduced an official carbon tax on 1 July 2012, but this was met with opposition from the general public.
• Match duration increased by 15%, and spectator attendance declined in parallel.
• Nadal dominated the clay court, yet Djokovic maintained superiority on hard surfaces.

Target: 15–25% of sentences per paragraph.

3. Complex sentence

One independent clause + one dependent clause (introduced by a subordinating conjunction: as, because, although, when, while, if, since, after, before, unless, until, whereas).

Use for: Causal reasoning, conditional statements, temporal ordering (the backbone of academic analysis).

Examples:

• As the Australian government recognised the necessity to significantly reduce greenhouse gas emissions, it introduced an official carbon tax on 1 July 2012.
• Although the dataset spans 121 seasons, only matches after 1968 include detailed set-level data.
• Because five-set matches impose greater physical demands, average rally length decreases in the fourth and fifth sets.

Target: 30–40% of sentences per paragraph (primary structure for academic prose).

4. Compound-complex sentence

Two or more independent clauses + one or more dependent clauses.

Use for: Sophisticated synthesis, multi-factor analysis, nuanced arguments.

Examples:

• As the Australian government recognised the necessity to significantly reduce greenhouse gas emissions, it introduced an official carbon tax on 1 July 2012, but this was met with opposition from the general public.
• While set durations vary considerably between Grand Slam events, the median match length has increased by 12 minutes since 2000, and this trend correlates with advances in racquet technology.
• Because the 1905–1968 era lacked professional circuits, participation remained limited to amateur players; however, match records from this period still provide valuable longitudinal data.

Target: 10–20% of sentences per paragraph (use sparingly for maximum impact).

Variation rules

Within a paragraph

1. Never place 3+ sentences of the same type consecutively 2. Vary sentence length:

• Short: 8–15 words (for impact)
• Medium: 16–25 words (for flow)
• Long: 26–40 words (for depth)

3. Each paragraph should contain at least 3 of the 4 sentence types 4. Vary paragraph length (2–8 sentences); uniform blocks signal AI

For detailed burstiness detection, semicolon limits, and paragraph length variation rules, see anti-ai-checklist.md §9.

Sentence openers (vary these)

Rule: No 3+ consecutive sentences beginning with the same opener type.

Common errors to prevent

Sentence fragments

A sentence missing subject, verb, or complete thought.

Watch out for: Sentences beginning with so, as, because, who, which, that, since these are often incomplete.

Run-on sentences

Two independent clauses joined without proper punctuation or conjunction.

Lack of clear meaning

Every sentence must be fully understandable when read in isolation. If a sentence requires mental gymnastics to parse, rewrite it more simply.

Paragraph cohesion model

[Topic Sentence — main point, often complex or compound-complex]
[Supporting Sentence 1 — evidence, often simple or complex]
[Supporting Sentence 2 — analysis, often complex]
[Supporting Sentence 3 — additional evidence or counter-argument, often compound]
[Concluding Sentence — link to broader argument or transition, often compound-complex]

Bad example (monotonous structure)

Nursing education states that measures should be in place to avoid infection. Also, that infection rates tend to soar when hygiene standards decrease. Appropriate steps should be taken to decrease these risks. It is suggested that medical staff are educated to understand these risks.

Problems: Same structure (simple/simple), same opener pattern ("X states", "Also, that"), same sentence length, no cohesion between sentences.

Good example (varied structure)

Nursing educators argue that strict measures should be implemented to avoid infection in medical institutions. There is also much evidence to demonstrate that infection rates rise dramatically when hygiene standards begin to fall. Therefore, it is argued that appropriate steps need to be in place to decrease and minimise these potential risks. Furthermore, aggressive steps should be taken to ensure that all staff maintain effective hygiene and infection control.

Improvements: Varied openers, mixed simple/complex/compound structures, varied sentence lengths, logical flow from claim → evidence → argument → recommendation.

Quick reference: conjunction inventory

Coordinating (FANBOYS): for compound sentences

for, and, nor, but, or, yet, so

Subordinating: for complex sentences

Cause/reason: because, since, as, given that, owing to the fact that Contrast: although, though, even though, whereas, while, whilst Condition: if, unless, provided that, on condition that Time: when, whenever, after, before, until, since, while, as soon as Purpose: so that, in order that Result: so ... that, such ... that

Transitional phrases (non-AI): for sentence openers

By contrast, More specifically, In parallel, To this end, From a different perspective, On closer examination, Upon further analysis, In quantitative terms, At the aggregate level, Within this framework, Across all conditions