Transparent evidence
The language model may assist with structured evidence extraction, but programmed rules determine the final category scores and risk bands.
EAIPAM scoring profile
Reproducibility protocol
Fingerprint
Calculate a SHA-256 hash for the exact uploaded file.
Version
Lock parser, rubric, model, prompt, dataset and reference snapshot.
Score
Apply fixed numerical rules to stored structured findings.
Preserve
Store the evidence and approved report as an immutable record.
Calibration and training governance
Administrators can upload verified human-drafted, AI-drafted, mixed or indeterminate manuscripts. Every record must include provenance, permission status, subject area and label confidence.
A newly uploaded example cannot change live assessments. It enters an experimental dataset, undergoes validation and becomes active only through a newly published EAIPAM training profile.
Responsible interpretation
EAIPAM reports evidence and editorial risk. It does not claim that stylistic patterns alone prove authorship by a particular model or tool. Reference integrity, scientific accuracy and citation-to-claim alignment remain the dominant assessment components.