[Re] Modeling Insect Phenology Using Ordinal Regression and Continuation Ratio Models

How do ordinal probability estimates and calibration change across held-out time periods in a rights-cleared dataset?

An evaluator controls time-based splits and ordinal scoring; model probabilities are checked for nonnegativity and normalization.

What you could produce

• Versioned protocol, input and environment manifest, and independent per-case comparison table including uncertainty and incomplete cases.

Before you use it

• Exact article-specific dependencies, data and build requirements remain uninspected.

Limits to keep in view

• No research code was executed; no independent scientific verification has been performed.
• The current qualified pilot is self-contained Python 3.13 with a 90-second author deadline. This article's environment has not been qualified for that path.
• Published source metadata and a historical review do not establish compatibility, successful reproduction, operator independence or current scientific correctness.
• The language/runtime named by the upstream source is outside the current qualified Python-only pilot.

Source and permission context

Boersch-Supan, Philipp H.. [Re] Modeling Insect Phenology Using Ordinal Regression and Continuation Ratio Models. ReScience C 7(1), #5; 10.5281/zenodo.5006005.

Rights need review. Review the scope and upstream conditions before reuse.

Still unresolved

• The associated code's exact license and version-specific third-party notices have not been independently checked.
• Data licenses, permissions, consent restrictions and redistribution conditions have not been independently checked.
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