13 KiB
QQcites Citation Ranking
Use this reference when a request has more than one claim, many local-note hits, or ambiguous citation choices.
Segmentation and Claim IDs
When the user provides a paragraph, manuscript section, or multiple sentences, create stable citable segments before searching.
- Use
S001,S002,S003for sentence or claim segments. - Preserve the user's original text for each segment.
- Split broad paragraphs into smaller claims when one sentence contains multiple citation needs.
- Skip purely connective wording unless the user asks to cite every sentence.
- For each segment, record:
claim_type: background, review-context, mechanism, material-property, method, characterization, performance, application, or limitation.entity: material, molecule, device, method, application, or phenomenon.relationship: improves, drives, coordinates, adsorbs, transports, converts, senses, stabilizes, limits, etc.context: stimulus, material system, measurement method, device condition, organism/model, or application boundary.boundary: only under a stated condition such as humidity range, light intensity, cell model, or target journal scope.
Generate 2-4 search queries per segment:
precise: entity + relationship + context + target metric.synonym: alternate names, abbreviations, Chinese/English equivalents, chemical formulas.broad: field or mechanism context if direct local matches are weak.method/performance: include measurement method, figure metric, or device parameter when the claim is quantitative.
For Chinese manuscript text, translate scientific concepts rather than the sentence literally. Keep standard formulas, acronyms, and material names unchanged.
Candidate Search Pattern
Search each claim with four groups of terms:
- Core nouns: material, molecule, device, disease, target, method, or phenomenon.
- Mechanism verbs: drives, activates, suppresses, coordinates, adsorbs, transports, degrades, detects, heals, oxidizes, reduces.
- Performance words: sensitivity, stability, conductivity, capacity, selectivity, efficiency, biocompatibility, degradation, response time.
- Synonyms and translations: Chinese terms, English terms, abbreviations, chemical formulas, and common aliases.
Use several narrow searches instead of one broad search. Example:
rg -n -i "MXene|Ti3C2|conductivity|electromagnetic shielding" "C:\Users\qyh15\Documents\Obsidian Vault\01 文献阅读"
Adjust the vault subfolder if QQnote-skill documents a different current literature-note folder.
Source Tiers and Routing
Use local sources before external sources, but record source reliability explicitly.
| Tier | Source | Use |
|---|---|---|
| T0 | User local Zotero, Obsidian literature notes, QQnote notes, local PDFs | Default first source and strongest grounding for this user's manuscripts |
| T1 | DOI/CrossRef metadata, publisher pages, PubMed when relevant | Metadata verification and official claim/source checking |
| T2 | Semantic Scholar, arXiv/bioRxiv/medRxiv when relevant | Broader discovery, citation graph, preprints |
| T3 | Google Scholar, general web pages, institutional pages, manually accessed CNKI/Wanfang | Last resort; label as incomplete or web-sourced |
Fallback routing:
- Search T0 with exact and synonym terms.
- If T0 is insufficient, verify or supplement with T1.
- If T1 is still insufficient, broaden with T2.
- Use T3 only when T0-T2 fail or the user explicitly asks for broad web search.
- Never let weak T3 evidence replace strong T0 evidence unless the local item is wrong, outdated, or not actually supportive.
DeepSeek Screening Prompt
When DeepSeek is available, pass only the manuscript claim and candidate snippets needed for ranking:
Task: Rank local literature-note candidates for supporting one manuscript sentence.
Manuscript sentence:
<sentence>
Candidate notes:
<numbered snippets with title/year/DOI/path if available>
For each candidate, judge:
1. relevance: strong support, partial support, background support, contradictory/limiting, metadata-only candidate, weak, unrelated
2. article type: review, primary research, method, unclear
3. whether it truly supports the sentence or only shares keywords
4. one-sentence reason
Return a ranked list. Prefer review articles for broad background claims, but prefer primary evidence for specific experimental or mechanistic claims.
Do not invent metadata or references not present in the candidates.
Support Grades
Use the smallest support grade that is defensible.
| Grade | Meaning | Good use |
|---|---|---|
| strong support | Directly tests or reviews the same core claim in a matching context | Specific mechanism, material property, method, or performance statements |
| partial support | Supports only part of the sentence, a narrower system, or a related condition | Claims that can be qualified or split |
| background support | Establishes field context but not the exact claim | Introduction, motivation, broad status statements |
| contradictory/limiting | Conflicts with or narrows the claim | Avoid as support; use for limitations or revise wording |
| metadata-only candidate | Title/metadata suggest relevance but abstract/full text has not been checked | Screening only; do not cite as support yet |
| weak | Shares keywords but does not support the sentence well | Usually exclude |
| unrelated | Not useful for the claim | Exclude |
Do not cite a metadata-only candidate as support until the abstract, note, publisher page, or local PDF has been checked.
Evidence Note Template
Use this template when ranking important citations, when the user asks why a paper was selected, or when the claim is high-risk:
Segment: S001
Claim: <original claim>
Candidate: <first author/year/title/journal/DOI/Zotero key>
Support grade: <strong/partial/background/contradictory/metadata-only/weak>
Evidence basis: <local note / Zotero metadata / abstract / main text p.X / figure caption / SI / publisher page>
Reasoning: <why it supports, partially supports, or fails to support the exact claim>
Caveat: <repeated reference, review-only, different material system, graph-only value, etc.>
Citation wording: <where or how to cite; suggest wording change if the manuscript overclaims>
Deduplication
Use DOI as the primary duplicate key.
- Normalize DOI by lowercasing, trimming whitespace, and removing
https://doi.org/. - Treat identical normalized DOI values as the same paper even if Zotero keys differ.
- If DOI is missing, compare Zotero key, normalized title, first author, and year.
- Normalize titles by lowercasing, removing punctuation and stopwords, and collapsing whitespace.
- Treat records as duplicates when the first-author surname matches and normalized-title token overlap is very high, approximately Jaccard similarity >= 0.90.
When duplicate records differ in metadata quality, prefer the record with DOI, complete journal/year/volume/pages, and a local PDF or QQnote note.
Citation Verification Mode
When the user asks to check an existing reference list, manuscript bibliography, or Zotero export, switch from recommendation mode to verification mode.
Classify each reference as:
verified: metadata matches DOI or official source.duplicate: same DOI/title appears more than once.mismatch: title, journal, year, author, or DOI conflicts with retrieved metadata.not_found: no reliable match in local library or external metadata.suspicious: likely typo, encoding problem, impossible year/pages, or journal mismatch.manual_needed: insufficient identifiers or ambiguous title.
Return a summary count plus a detail table with DOI/Zotero key, issue, and suggested correction. Do not silently rewrite a bibliography without showing what changed.
Tie-Breaking
Rank candidates using this order:
- Direct support for the exact claim.
- Stronger article type for the sentence purpose:
- review first for broad field status, motivation, classification, mechanisms overview, or "recent advances" wording.
- primary research first for exact material composition, synthetic method, measurement, performance number, biological effect, or device result.
- Newer review if two reviews provide similar background coverage.
- Higher-quality note evidence: abstract plus detailed AI note beats title-only or metadata-only matches.
- DOI and complete Zotero metadata available.
Final Table Template
Use this compact table for most answers:
| Rank | Citation candidate | Type | Strength | Why it fits | Suggested use |
|---|---|---|---|---|---|
| 1 | Title. Journal, Year. DOI: ... | review | direct/background | ... | Cite after clause ... |
If a sentence has no strong local match, write No strong local match found and list the closest weak candidates separately.
For multi-segment citation work, use stable segment IDs:
| Segment | Claim type | Best candidate | Support grade | Evidence basis | Suggested use |
|---|---|---|---|---|---|
| S001 | background | Title. Journal, Year. DOI: ... | background support | local note + abstract | Cite after broad field sentence |
Performance Comparison Tables
When the user asks for a literature performance table, define hard inclusion criteria before recommending papers. Typical criteria include material family, stimulus type, whether the paper is primary research, whether the target metric is reported, whether units can be normalized, and whether the item is present in local Zotero/Obsidian. Put only papers that satisfy the table criteria in the main table. Papers that report only angle, displacement, speed, demonstration photos, or concept-level behavior should be listed as supplemental or non-comparable unless the user explicitly wants them.
Extract performance parameters from the local Zotero PDF whenever possible. Record the evidence level for every number: main text, figure caption, supporting information, graph digitization, abstract only, or calculated. If a value requires graph reading, label it as needs digitization until the figure has actually been digitized. Do not present graph-estimated values as directly reported values.
Normalize units before comparison. Use cm^-1 for curvature (1 mm^-1 = 10 cm^-1) and mW cm^-2 for light intensity (1 W cm^-2 = 1000 mW cm^-2). If the paper reports total optical power rather than power density, label it as total power, not normalized and do not convert it to mW cm^-2 without the illuminated area. Keep maximum temperature, temperature rise, and photothermal conversion efficiency as separate metrics.
For angle-only actuator data, convert to curvature only when the effective bending length is known and the geometry makes the conversion defensible. Use kappa = theta(rad) / L(cm) and record the length and source. If the effective length is missing, write not convertible from main text rather than forcing a number.
Default table triage:
main-table usable: primary research, target material/stimulus, directly reports the target metric or supports a defensible unit conversion.supplemental comparison: relevant material/stimulus but reports a different metric such as angle, speed, displacement, or application behavior.not recommended: review, wrong stimulus, non-target material family, no performance metric, or only broad background relevance.
Maintain a manuscript-specific performance-table ledger in addition to the citation ledger. Track table name, DOI, Zotero key, title, material system, metric values, evidence level, whether it was used in the main or supplemental table, and any caveats such as figure only, angle-only, or total power.
Source Map for Original-Paper Parameters
When extracting parameters from PDFs or full texts, maintain a source map so the value can be rechecked later.
Minimum source-map fields:
| Field | Meaning |
|---|---|
value_id |
Stable ID such as P001, P002 |
paper |
title, DOI, Zotero key |
parameter |
curvature, light intensity, response time, Tmax, PTCE, RH range, etc. |
value |
extracted numeric value and unit |
source_level |
main text, figure caption, SI, graph digitization, abstract only, calculated |
location |
page, figure, table, supplementary note, or caption |
snippet |
short local text around the value when available |
conversion |
formula and assumptions if calculated |
caveat |
figure-only, total power, angle-only, missing area, repeated paper, etc. |
If the user asks follow-up questions about a table value, answer using the source map rather than memory.
Batch Mode for Long Manuscripts
When the input has more than about 10 citable segments, use batch mode.
- 1-10 segments: process normally and include inline evidence notes.
- 11-25 segments: split into batches of about 10, return a compact summary table, and keep a ledger/source-map artifact if file editing is available.
- 26+ segments: split by manuscript section first, process section by section, then merge and deduplicate by DOI.
For long runs, avoid writing long explanations for every weak candidate. Focus detailed notes on missing, contradictory, repeated, or high-risk segments.
Reference Export
When the user asks for export, prepare metadata for one reference-manager format:
- RIS for Zotero/EndNote/Mendeley interchange.
- BibTeX for LaTeX/manuscript projects.
- ENW when EndNote tagged export is requested.
Do not invent missing fields. If DOI, volume, issue, or pages are unavailable, leave the field blank and mark metadata incomplete. Deduplicate exported records by DOI before writing an export file.