From informs-journal-on-computing-skills
Runs computational experiments and assembles reproducible code/data deposits for IJOC manuscripts. Turns a designed protocol into defensible, reproducible results with statistical comparisons, performance profiles, and handling of tuning/seed/benchmark artifacts.
How this skill is triggered — by the user, by Claude, or both
Slash command
/informs-journal-on-computing-skills:ijoc-data-analysisThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
- The protocol is designed and you are now **running experiments** and interpreting results
IJOC's distinctive risk is a result that is real on the page but an artifact underneath. Pre-empt the three ways a referee will attack it.
Means and "X is fastest" are not enough. Use the comparisons that suit computational data:
ijoc-theory-development.Report optimality gaps with their definition, dual bounds where available, and time limits explicitly (a "solved" count is meaningless without the limit).
Accepted IJOC papers deposit artifacts in the INFORMSJoC GitHub organization, and the deposit is part of the contribution — design it to reproduce the paper. Concretely (检索于 2026-06;以官网为准):
github.com/INFORMSJoC/2019.0000) and replace placeholders with your manuscript ID XXXX.YYYY.README.md (with a ## Cite section as the first subheading, using DOI 10.1287/ijoc.XXXX.YYYY.cd), LICENSE, and AUTHORS.src/, data/ (with documented provenance), scripts/ (to replicate experiments), results/, docs/.requirements.txt, Manifest.toml, environment files). A best-faith reproducibility effort is expected even if exact bit-reproduction is not.vXXXX.YYYY) is archived and a code DOI (….cd) is minted alongside the article DOI — so the deposited state must match the published results.The README's replication section should let a reader regenerate each table/figure from scripts/. If your results/ directory maps one-to-one to the paper's exhibits, the reproducibility reviewer's job — and yours during the R&R — becomes mechanical.
## Cite)/LICENSE/AUTHORS; src/data/scripts/results; pinned deps; seedsresults/ maps to the paper's tables/figures; scripts regenerate them【Journal】INFORMS Journal on Computing
【Skill】ijoc-data-analysis
【Headline result】the computational win, stated with its metric
【Artifact controls】default+tuned / #seeds+dispersion / full instance set
【Statistics】performance profile + Wilcoxon (+ MC control)? [Y/N]
【Scaling vs. theory】[consistent / discrepancy noted]
【Deposit】template/README+Cite/LICENSE/AUTHORS/scripts/seeds ready? [Y/N]
【Next skill】ijoc-contribution-framing
npx claudepluginhub brycewang-stanford/awesome-journal-skills --plugin informs-journal-on-computing-skillsDesigns fair, reproducible experimental protocols for IJOC manuscripts. Activates when method choice, baselines, and computational-experiment design need alignment before scaling up runs.
Runs and reports the computational study for an Operations Research manuscript, including benchmarks, baselines, statistical care for stochastic output, and the ORJournal reproducibility workflow.
Strengthens IJCAI/ECAI reproducibility evidence using the official reviewer rubric. Maps contributions (algorithms, theory, datasets, experiments) to credible/convincing ratings and guides evidence drafting.