ICDM Paper Review & Author Response

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Prepares academic manuscripts for ICDM peer review by pre-answering reviewer critiques and drafting anonymity-safe author rebuttals.

The ICDM Author Response skill helps researchers navigate the unique review dynamics of the IEEE International Conference on Data Mining (ICDM), where author rebuttals are traditionally not offered. It guides authors to preemptively address critical reviewer questions—such as baseline tuning fairness, run variance, data leakage, and empirical scalability—directly within the submitted manuscript and anonymized artifacts. If a specific conference edition opens a rebuttal window, the skill assists in drafting concise, evidence-backed, and triple-blind anonymity-safe responses that resolve reviewer misunderstandings without introducing unsupported claims.

주요 기능

01Pre-submission critique audit covering baselines, variance, leakage, scale, and validity
02Evidence-grounded response mapping referencing existing tables and sections
03Contingency rebuttal drafting for conference editions with open response windows
041,079 GitHub stars
05Triple-blind anonymity compliance checks to prevent de-anonymization risks
06Structured readiness checklist to eliminate unanswerable post-submission flaws

사용 사례

01Auditing data mining experiments for baseline fairness, variance reporting, and temporal leakage
02Preemptively hardening ICDM research paper drafts against common reviewer objections before submission
03Formulating concise, evidence-based author responses when an ICDM rebuttal window is provided