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 New Phytologist or deciding whether a plant-science manuscript fits this venue. Encodes the journal's fit, the integrative conceptual-advance and whole-plant/ecosystem-scale bar, evidence and data-deposition expectations, house style, official-submission re-check, and desk-reject 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。
New Phytologist, published by the New Phytologist Foundation, is a plant-science journal with a long-standing strength in plant ecology, physiology, environmental interactions, and symbiosis — mycorrhizal and other plant–microbe relationships, whole-plant function, and processes that scale from organism to community and ecosystem. Its defining expectation is a conceptual advance with integrative breadth: a study that changes how a process is understood by connecting levels of organization, rather than a tightly bounded mechanistic result. A study whose contribution is a single gene-to-function molecular mechanism with no physiological, ecological, or whole-organism reach usually fits a cellular/molecular journal better. This skill is a fit / venue-selection / re-framing tool. It does not replace the journal's current author guidelines. Before submitting, re-check the live New Phytologist author guidance.
the-plant-journal and needs the
ecology/physiology-breadth versus molecular-mechanism distinction made explicit.../../resources/source-basis.md and
../../resources/official-source-map.md; start from the official source anchors, then
cite the current New Phytologist page you checked.the-plant-journal.nature-plants.field-crops-research.global-change-biology.agriculture-ecosystems-and-environment.[Fit] High / Medium / Low (one-line reason)
[Target] New Phytologist
[Topic tags] <2–3 closest integrative plant topics>
[Conceptual advance] <how it connects scales or generalizes beyond one system>
[Method/evidence] <does design + replication + data deposition clear New Phytologist's bar?>
[Top risk] <the single most likely reason for rejection>
[Official items to re-check] <article type / statistics / data + accession policy / disclosures>
[Re-route suggestion] <if not a fit, a better-matched 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.
中文简介正在准备中。当前显示原文说明。
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.
中文简介正在准备中。当前显示原文说明。