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Record W2091048781 · doi:10.1515/cclm.2010.313

Nucleic acid reference materials (NARMs): definitions and issues

2010· review· en· W2091048781 on OpenAlexaff
Deborah Payne, Cyril Mamotte, David Gancberg, Mario Pazzagli, RON H. N. VAN SCHAIK, Heinz Schimmel, François Rousseau

Bibliographic record

VenueClinical Chemistry and Laboratory Medicine (CCLM) · 2010
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMolecular Biology Techniques and Applications
Canadian institutionsUniversité LavalCentre hospitalier universitaire de Québec
Fundersnot available
KeywordsHarmonizationContext (archaeology)Computer scienceReference valuesMedical physicsData scienceMedicineBiology

Abstract

fetched live from OpenAlex

Molecular diagnostics is one of the most rapidly growing areas of laboratory medicine. This rapid growth of clinical molecular tests has outpaced the availability and development of reference methods and reference materials. Such methods and materials are important for the development, validation, and interpretation of diagnostic methods and tests. Yet, there is a lack of harmonization between the numerous international organizations currently either certifying or defining reference materials. The objective of this position paper is to review and clarify the definition, attributes and applications for the use of reference materials in the context of molecular diagnostics.

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)0.007
metaresearch head score (Gemma)0.007
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: Review · Consensus signal: Review
Teacher disagreement score0.007
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.007
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0060.007
Science and technology studies0.0010.004
Scholarly communication0.0030.005
Open science0.0030.002
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0020.006

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 head0.088
GPT teacher head0.418
Teacher spread0.330 · 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
GenreReview

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
Published2010
Admission routes1
Has abstractyes

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