Justifying The Lack of Incurred Sample Reproducibility in A Study: Considerations and Strategies
Bibliographic record
Abstract
In 2012 with the issuance of its Guideline on Bioanalytical Method Validation, the European Medicine Agency (EMA) made the incurred sample reproducibility (ISR) assessment a requirement for studies to be submitted to European authorities. Since then 2012, European agencies have started to issue deficiencies to pharmaceutical companies for lack of ISRs in studies submitted recently but performed prior to the issuance of the 2012 Guideline. It now becomes the applicant's responsibility to justify scientifically the departure from the new guideline even for less recent studies. This article details the different strategies to provide an adequate justification for the absence of ISR data in studies performed prior to February 2012 but submitted to European agencies after that date.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.769 | 0.773 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.009 | 0.004 |
| Science and technology studies | 0.005 | 0.021 |
| Scholarly communication | 0.016 | 0.011 |
| Open science | 0.011 | 0.011 |
| Research integrity | 0.022 | 0.015 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".