Abstract Structure Guide
An effective academic abstract contains five structural elements that together tell a complete research story. This guide defines each element, how to detect it, and what makes it strong or weak.
Five-Element Model
1. Background
Purpose: Establish the research context — the real-world problem, knowledge gap, or motivation.
Detection markers (EN): "however", "remains unclear", "limited research", "growing interest", "challenge", "gap", "despite", "little is known", "increasingly important"
Detection markers (ZH): "然而", "尚不清楚", "研究不足", "日益增长", "挑战", "空白", "尽管", "鲜有研究"
Quality criteria: Moves from broad context to specific gap in 1-2 sentences. A vague background restates the field name without identifying a gap.
2. Objective
Purpose: State what this specific study aims to answer or accomplish.
Detection markers (EN): "this study aims", "we investigate", "the purpose of", "this paper presents", "we propose", "our goal", "in this work", "we address", "this research examines"
Detection markers (ZH): "本文旨在", "本研究探讨", "本文提出", "研究目的", "为此我们", "本工作", "本文研究"
Quality criteria: Specific and falsifiable. A vague objective says "we study X" without specifying what aspect or what question about X.
3. Methods
Purpose: Describe the approach, data, tools, or analytical framework used.
Detection markers (EN): "we propose", "using", "dataset", "participants", "method", "approach", "framework", "model", "algorithm", "collected", "trained", "evaluated", "sample", "experiment"
Detection markers (ZH): "采用", "方法", "数据集", "样本", "模型", "算法", "框架", "实验", "训练", "评估"
Quality criteria: Names the specific technique, data source, or experimental setup. Missing methods make the abstract feel like an opinion piece.
4. Results
Purpose: Report the key findings with concrete data.
Detection markers (EN): "results show", "achieved", "outperforms", "accuracy", "improved", "reduced", "found that", "demonstrates", "significant", numbers, percentages, p-values
Detection markers (ZH): "结果表明", "达到", "优于", "准确率", "提高", "降低", "发现", "显著", numbers
Quality criteria: Must contain at least one quantitative finding (number, percentage, ratio, or comparative statement with magnitude). A results section without numbers is classified as VAGUE.
5. Conclusion / Significance
Purpose: State the contribution, implications, or practical value of the findings.
Detection markers (EN): "our findings suggest", "contributes to", "implications", "demonstrates that", "can be used", "enables", "provides", "advances", "potential"
Detection markers (ZH): "研究发现表明", "为...提供", "有助于", "具有...意义", "可用于", "推动", "贡献"
Quality criteria: Goes beyond restating results — connects findings to the broader field or practice. A hollow conclusion just repeats the results in different words.
Common Defect Patterns
| Defect | Description | Typical fix |
|---|---|---|
| Missing background | Jumps straight to "We propose..." | Add 1 sentence on the problem context |
| Vague objective | "We study deep learning for NLP" | Specify: "We investigate whether... improves..." |
| No methods | Describes results without explaining how | Add the core technique and data source |
| Data-free results | "Our method performs well" | Add a key metric: "achieves 94.2% F1" |
| Echo conclusion | Restates results verbatim | Add implication: "enabling real-time..." |
Word Count Guidelines
| Context | Language | Range |
|---|---|---|
| Default (no venue specified) | English | 150–250 words |
| Default (no venue specified) | Chinese | 200–300 characters |
| IEEE conference | English | 150–200 words |
| ACM conference | English | 150–250 words |
| NeurIPS/ICML | English | ≤ 200 words (strict) |
| Chinese thesis (GB/T) | Chinese | 300–500 characters |
Venue-specific limits override defaults. Check catalog.md for exact requirements.
Diagnostic Output Format
The analyzer outputs a per-element diagnosis:
Background: ✅ PRESENT — "Despite growing interest in X, the impact of Y remains unclear."
Objective: ⚠️ VAGUE — "This paper studies X." → Suggestion: specify the research question
Methods: ✅ PRESENT — "We propose a framework based on Z, evaluated on dataset W."
Results: ❌ MISSING — No quantitative findings detected → Add key metrics
Conclusion: ⚠️ VAGUE — Restates results without implications → Add practical significance学位论文摘要骨架（thesis 模型）
上面的五要素模型是会议/期刊小论文口径。中文学位论文（尤其工科博士）摘要遵循一套不同的 骨架结构：不是 Background/Objective/Methods/Results/Conclusion 五段，而是"对象定位 → 痛点 → 总起句冒号收束 → 编号工作段 → 可选收尾段"。analyze_abstract.py 的 --model thesis 为默认， 诊断这套骨架；--model five 保留上面的五要素模型作后备（本技能只服务学位论文，五要素模型对 博士摘要会系统性误报，如 Results 无数值判 MISSING，而合规博士摘要常定性收口）。
骨架顺序（宏观）
① 对象定位首句："X 是……" / "X 产生于……"（研究对象为主语，非方法开头）
② 痛点/挑战段："然而，……难以/挑战/瓶颈……"
③ 总起句 + 冒号收束："本文主要研究工作/创新点如下："
④ 编号工作段 (1)(2)(3)…：每段"针对……问题，提出/建立……，实验/应用表明……"
⑤ 可选收尾段：综述成果/工程应用（"优化/工程应用"类论文常见，非必需）段落数 = 背景段(1~2) + 工作段(编号数) + 可选收尾段。
与五要素模型的关系
| 维度 | 五要素模型（--model five） | 学位论文骨架（--model thesis，默认） |
|---|---|---|
| 适用 | 会议/期刊小论文 | 中文博士/硕士学位论文 |
| 主体 | Background/Objective/Methods/Results/Conclusion 五段 | 编号工作段 (1)(2)(3)… |
| 数值 | Results 无数值判 VAGUE/MISSING | 数值可选（4/5 定性收口合规），出现才查稳健表述 |
| 字数 | EN 150~250 词 / ZH 200~300 字 | 对齐 check_spec 燕山常量：博士 900~1200 字 / 硕士 500~650 字 |
字数阈值由 --degree {doctor,master} 切换（默认 doctor），--max-chars 可覆盖上界。
T-* 分级规律表
诊断项对应 research abstract-patterns.md 编号；★ 标记（≥4/5）为默认告警，2~3/5 规律仅 Info：
| 检查码 | 内容 | 级别 | 溯源 |
|---|---|---|---|
| T-OPEN | 首句以研究对象为主语定位，非方法开头 | Warning | ★A1 5/5 |
| T-PAIN | 存在痛点/挑战句（难以/挑战/尚未/瓶颈） | Warning | ★A2 5/5 |
| T-LEAD | 编号段前有总起句且以"："收束 | Warning | ★A4 5/5 |
| T-ENUM | 主体为 (1)(2)… 编号工作段，段数与编号一致 | Warning | ★A5 5/5、D4 |
| T-VERIFY | 验证方式点名（仿真/实测/生产数据/现场应用），非空泛"验证有效" | Warning | ★C2 5/5 |
| T-ABBR | 缩略语首现即定义中英全称 | Warning | ★E3 5/5 |
| T-INNOV | 出现创新表述（创新/首次/新方法 或编号工作段本身） | Warning | web A3 校规 |
| T-TOC-STYLE | 非目录式摘要 / 背景铺陈不过长 | Warning | web A10 软性 |
| T-PROB | 各工作段以问题导向短语开头（全篇 <50% 才报） | Info | ★B1 |
| T-VERB | 方法动词属规范集（提出/建立/设计/构建/研究/采用） | Info | ★B4 |
| T-NUM-HEDGE | 数值指标带"约/以上/区间"稳健表述（有数值才查） | Info | C3 2/2 |
| T-KW-FIRST | 首个关键词≈研究对象/过程名 | Info | ★D2 |
| T-VOICE | 只查"我/我们/笔者"；"本文/本论文"合法 | Info | web A6 |
中英摘要一致性（--bilingual）
thesis 模式加 --bilingual 时额外比对英文 Abstract 与中文摘要：
| 检查码 | 内容 | 级别 | 溯源 |
|---|---|---|---|
| B-ORD | 首先/其次/然后/最后 ↔ First/Second/Then/Finally 数量与顺序对齐 | Warning | ★F3 5/5 |
| B-NUM | 中英数值 token 集合一致 | Error（数值不一致是硬伤） | ★F1；web A9 |
| B-ENUM | 编号工作段条数一致 | Warning | ★F1 |
| B-LEN | 英文摘要缺失/过短 | Warning | web A9 |
| B-SEM | 逐句/逐要素语义对应（[LLM] lane，报告给对照提示词） | — | ★F1 |
时态/语态（★F2 英摘方法句一般现在时被动）不在此实现：deai 模块已有英文摘要区域门控的 时态检测（tense-guide-zh.md + deai_check），--bilingual 报告尾注指路 deai， 避免双实现漂移（deai trace 不流入本模块）。
Constraints
- Never alter the author's core claims or fabricate data
- Never add results or conclusions not present in the original text
- Preserve all citations, labels, and math environments
- Mark all modifications with brackets: [ADDED: ...] or [REVISED: ...]