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Record W3000541973 · doi:10.1088/0026-1394/57/1a/08004

Final report of CCQM-K86.c. Relative quantification of genomic DNA fragments extracted from a biological tissue

2020· article· en· W3000541973 on OpenAlexaffabout
Zoltán Mester, Philippe Corbisier, Stephen L. R. Ellison, Yunhua Gao, Chunyan Niu, Vincent Tang, Foo-wing Lee, Melina Pérez Urquiza, Angel Ramirez Suárez, Malcolm Burns, Mojca Milavec, Kanjana Wiangnon, Kate R. Griffiths, Jacob McLaughlin, Sachie Shibayama, Akiko Takatsu, Müslüm Akgöz, Maxim Vonsky, John Emerson Leguizamón Guerrero

Bibliographic record

VenueMetrologia · 2020
Typearticle
Languageen
FieldMedicine
TopicViral gastroenteritis research and epidemiology
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsMetrologyMutual recognitionLibrary scienceChinaNational laboratoryPolitical scienceEngineeringMathematicsComputer scienceBusinessStatisticsLawEngineering physics

Abstract

fetched live from OpenAlex

Key comparison CCQM-K86.c was performed to demonstrate the capacity of National Metrology Institutes (NMIs) and Designated Institutes (DIs) in the determination of the relative quantity of two specific genomic DNA fragments present in a canola powder. The study provides direct support for the following measurement claim: "Quantification of the ratio of the number of copies of specified intact sequence fragments of a length up to 150 nucleotides following extraction from an unprocessed, high fat/oil ground seed matrix, with a copy number ratio from 0.001 to 1". The study was carried out under the auspices of the Nucleic Acids Working Group (NAWG) of the Consultative Committee for Amount of Substance: Metrology in Chemistry and Biology (CCQM) and was jointly coordinated by the National Research Council of Canada (NRC) and the EU Joint Research Centre, Geel (JRC). The following laboratories (in alphabetical order) submitted measurement results in this key comparison study: Centro Nacional de Metrología, Mexico ("CENAM"); D.I. Mendeleyev Institute of Metrology, Russia ("VNIIM"); EU Joint Research Centre, Geel (JRC); Hong Kong Government Laboratory ("GLHK"); Instituto Nacional de Metrología de Colombia ("INM"); LGC (United Kingdom); National Institute of Biology, Slovenia ("NIB"); National Institute of Metrology, P.R. of China ("NIM China"/"NIMC" [figures]); National Institute of Metrology, Thailand (NIMT); National Measurement Institute, Australia ("NMIA"); National Metrology Institute of Japan, AIST, Japan ("NMIJ"); National Metrology Institute of Turkey ("TÜBITAK"). Main text To reach the main text of this paper, click on Final Report . Note that this text is that which appears in Appendix B of the BIPM key comparison database kcdb.bipm.org/ . The final report has been peer-reviewed and approved for publication by the CCQM, according to the provisions of the CIPM Mutual Recognition Arrangement (CIPM MRA).

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)0.016
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.045
Threshold uncertainty score0.151

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.021
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0050.001
Scholarly communication0.0040.001
Open science0.0050.003
Research integrity0.0050.002
Insufficient payload (model declined to judge)0.0450.053

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 head0.142
GPT teacher head0.362
Teacher spread0.221 · 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 designBench or experimental
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

Citations6
Published2020
Admission routes2
Has abstractyes

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