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.
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Use when targeting the Bulletin of the American Meteorological Society (BAMS) or deciding whether a broad-interest atmospheric/oceanic/hydrologic-sciences contribution fits this venue. Encodes the journal's review-and-community positioning, the broad-audience-significance bar, synthesis and field-campaign expectations, AMS house style, official-submission re-check, and misfit heuristics.
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实测评分 未实测
查看安装方法安装前可以查看交给 AI 代理的指令内容。
The Bulletin of the American Meteorological Society (BAMS) is the AMS flagship for broad-interest content addressed to the entire atmospheric, oceanic, and hydrologic-sciences community: major review and synthesis articles, overviews of field campaigns and large research programs, and community pieces such as essays, meeting and workshop summaries, and policy- or education-relevant commentary. It is best understood as a review and community venue, not a home for narrow primary research — much of its substantive content is commissioned or developed in dialogue with editors, and every article must speak across sub-disciplines rather than to one specialist group. A focused original-research result, no matter how solid, generally belongs in a topical AMS research journal instead. 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 BAMS author instructions and article-type definitions.
journal-of-climate for a climate-science manuscript.../../resources/source-basis.md and
../../resources/official-source-map.md; start from the AMS anchors, then cite the current
BAMS page you checked.journal-of-climate (topical AMS research venue).journal-of-hydrology or water-resources-research.agricultural-and-forest-meteorology.limnology-and-oceanography.nature-climate-change or nature-geoscience.[Fit] High / Medium / Low (one-line reason)
[Target] Bulletin of the American Meteorological Society (BAMS)
[Article type] <review / synthesis / campaign-overview / program / essay / summary>
[Community significance] <why it matters across the whole community, not one specialty>
[Synthesis/breadth] <does coverage + accessibility + community resource clear the BAMS bar?>
[Commissioning note] <is editor scoping or a pre-submission inquiry advisable?>
[Top risk] <the single most likely reason for rejection>
[Official items to re-check] <article type / capsule summary / scoping / data policy / disclosures>
[Re-route suggestion] <if narrow research, a topical research venue>
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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.
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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.
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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.
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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.
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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.
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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.
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