Use when packaging AAAI code, data, multimedia appendices, technical appendices, reproducibility evidence, and post-acceptance artifact releases without violating double-blind or immutable-supplement rules.
日本語の概要は準備中です。原文の説明を表示しています。
Use when targeting Geology (GSA) or deciding whether a short, high-impact geoscience research letter fits this venue. Encodes the journal's broad-significance-in-tight-length fit, the novelty and rapid-communication bar, GSA house style, official-submission re-check, and desk-reject heuristics.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
Geology is the Geological Society of America's flagship outlet for short, high-impact research letters across the geosciences. The defining expectation is a contribution that is at once novel, broadly significant, and concisely framed for a wide geoscience audience within a tight length limit — a result that changes how a broad readership thinks about an earth process, delivered rapidly. The constraint is as much editorial as scientific: the science must be both important and compressible to a few pages, with the significance legible to non-specialists. A thorough but incremental study, a regional report without wide implications, or a paper that genuinely needs full article length to make its case is a poor fit, regardless of quality. This skill is a fit / venue-selection / re-framing tool. It does not replace the journal's current author guidance. Before submitting, re-check the live Geology / GSA author instructions and data policy.
earth-and-planetary-science-letters
(longer quantitative process article).../../resources/source-basis.md and
../../resources/official-source-map.md; start from the GSA/Geology anchors, then cite the
current Geology page you checked.earth-and-planetary-science-letters.nature-geoscience.communications-earth-and-environment.geophysical-research-letters.earth-system-science-data.[Fit] High / Medium / Low (one-line reason)
[Target] Geology (GSA)
[Topic tags] <2–3 closest geoscience topics>
[Broad significance] <why a wide geoscience audience should care, in one line>
[Fits-the-format] <can the result stand within the short-letter limit without over-reach?>
[Top risk] <the single most likely reason for rejection>
[Official items to re-check] <length/figure limits / GSA data repository / disclosures>
[Re-route suggestion] <if not a fit, a better-matched venue>
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Use when packaging AAAI code, data, multimedia appendices, technical appendices, reproducibility evidence, and post-acceptance artifact releases without violating double-blind or immutable-supplement rules.
日本語の概要は準備中です。原文の説明を表示しています。
Use when drafting an AAAI author response (rebuttal) under the single short character-limited author-feedback window, the no-URL rule, no-new-results guidance, AI-generated-review handling, and the AAAI two-phase review process where Phase-2 papers receive one feedback round before SPC/AC discussion.
日本語の概要は準備中です。原文の説明を表示しています。
Use when preparing an accepted AAAI paper for camera-ready source submission to AAAI Press, including proceedings page limits, two-column template compliance, copyright transfer, purchased extra technical pages, deanonymization, registration, oral or poster presentation, and final public artifact release.
日本語の概要は準備中です。原文の説明を表示しています。
Use when designing or auditing AAAI experiments for the broad-AI program committee, including baselines, ablations, statistical significance, robustness, human evaluation, AI-for-Social-Impact and alignment/safety evidence, compute and cost reporting, and reproducibility-checklist alignment for Phase-1 survival.
日本語の概要は準備中です。原文の説明を表示しています。
Use when positioning an AAAI paper's novelty against archival work, contemporaneous arXiv or workshop papers, and AAAI/IJCAI/NeurIPS/ICML/ICLR neighbors across the broad AI scope, while staying inside AAAI's dual-submission and AI-as-source policy constraints and writing a related-work section legible to non-specialist reviewers.
日本語の概要は準備中です。原文の説明を表示しています。
Use when strengthening an AAAI paper's reproducibility checklist (placed after references), experimental traceability, seed and hyperparameter reporting, compute and cost disclosure, dataset access and licensing, code/data ZIP readiness, and the claim-to-evidence map that Phase-1 reviewers use to judge rigor across AAAI's broad AI scope.
日本語の概要は準備中です。原文の説明を表示しています。