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Record W2745853122 · doi:10.5740/jaoacint.smpr2017_013

AOAC SMPR® 2017.013:Standard Method Performance Requirements (SMPRs) for Determination of Vitamins K1 and K2 in Dietary Supplements and Dietary Ingredients

2017· article· en· W2745853122 on OpenAlexaff
Inger Reidun, Gisele Atkinson, Sneh Bhandari, Neal E. Craft, Adam Horkey, Adam J. Kuszak, J. Andreas Lippert, Elizabeth Mudge, Kate Rimmer, Aniko M Sólyom, William Sommer, John Szpylka, Jason Lynn Wubben, Jinchuan Yang, Hong You

Bibliographic record

VenueJournal of AOAC International · 2017
Typearticle
Languageen
FieldNursing
TopicVitamin K Research Studies
Canadian institutionsBritish Columbia Institute of Technology
Fundersnot available
KeywordsDietary supplementFood scienceBiotechnologyTraditional medicineMedicineChemistryBiology

Abstract

fetched live from OpenAlex

Inger Reidun, Gisele Atkinson, Sneh Bhandari, Neal Craft, Adam Horkey, Adam Kuszak, J Andreas Lippert, Elizabeth Mudge, Kate Rimmer, Aniko Solyom, William

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 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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.221
Threshold uncertainty score0.617

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.076
GPT teacher head0.434
Teacher spread0.357 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations1
Published2017
Admission routes1
Has abstractyes

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