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Record W2570196790 · doi:10.5740/jaoacint.smpr2016.017

AOAC SMPR 2016.017:Standard Method Performance Requirements (SMPRs)for Quantitative Measurement of Vitamin B12 in Dietary Supplements and Ingredients

2017· article· en· W2570196790 on OpenAlexaff
Richard B. van Breemen, Joseph M. Betz, Lisa H. Evans, April Hall, Martha Jennens, Rachel Kreider, Adam J. Kuszak, Elizabeth Mudge, Punam Patel, Catherine A. Rimmer, Brian T Schaneberg, Anand Sheshadri, Aniko M Sólyom, John Szpylka, Denise Lowe Walters, Tyler White, Jinchuan Yang, Kurt Young, Garrett Zielinski, Scott G Coates

Bibliographic record

VenueJournal of AOAC International · 2017
Typearticle
Languageen
FieldMedicine
TopicFolate and B Vitamins Research
Canadian institutionsBritish Columbia Institute of Technology
Fundersnot available
KeywordsVitamin B12Dietary supplementVitaminFood scienceMedicineBiotechnologyChemistryBiologyInternal medicine

Abstract

fetched live from OpenAlex

Richard van Breemen, J Betz, Lisa Evans, April Hall, Martha Jennens, Rachel Kreider, Adam Kuszak, Elizabeth Mudge, Punam Patel, Catherine Rimmer, Brian T S

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.113
metaresearch head score (Gemma)0.147
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.113
Threshold uncertainty score0.599

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1130.147
Meta-epidemiology (narrow)0.0050.004
Meta-epidemiology (broad)0.0040.006
Bibliometrics0.0120.006
Science and technology studies0.0070.004
Scholarly communication0.0050.003
Open science0.0120.006
Research integrity0.0190.005
Insufficient payload (model declined to judge)0.0110.022

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 head0.132
GPT teacher head0.452
Teacher spread0.320 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreMethods

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".

Quick stats

Citations7
Published2017
Admission routes1
Has abstractyes

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