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Record W2139470111 · doi:10.4155/bio.09.108

Incurred Sample Reproducibility: Views and Recommendations by the European Bioanalysis Forum

2009· article· en· W2139470111 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBioanalysis · 2009
Typearticle
Languageen
FieldImmunology and Microbiology
TopicBiosimilars and Bioanalytical Methods
Canadian institutionsAbbott (Canada)
Fundersnot available
KeywordsBioanalysisSample (material)SafeguardingReproducibilityComputer scienceProcess (computing)Data scienceMedicineChromatographyChemistry

Abstract

fetched live from OpenAlex

Following intensive discussions, review, alignment of procedures and multiple surveys among their member companies, the European Bioanalysis Forum (EBF) is providing a recommendation on how to integrate incurred sample reproducibility (ISR) in the bioanalytical process. The recommendation aims to provide guidance throughout the lifecycle of a validated method, including the application of the method in study support. In its recommendation, the EBF considers both the internal discussions with EBF member companies, as well as the input provided in international meetings where ISR was discussed. The ultimate goal of the EBF recommendation is to ensure that bioanalytical methods can provide accurate and reproducible concentration data for pharmacokinetic and/or toxicokinetic evaluation, without any compromise, while safeguarding the optimal use of laboratory resources.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.958
Threshold uncertainty score0.984

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.038
GPT teacher head0.314
Teacher spread0.276 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it