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Record W4360600102 · doi:10.1007/s00122-023-04253-w

Updated guidelines for gene nomenclature in wheat

2023· article· en· W4360600102 on OpenAlexafffund
Scott A. Boden, R. A. McIntosh, Cristóbal Uauy, Simon G. Krattinger, Jorge Dubcovsky, William J. Rogers, X. C. Xia, Е. Д. Бадаева, Alison R. Bentley, Gina Brown‐Guedira, Mario Cáccamo, Luigi Cattivelli, Parveen Chhuneja, James Cockram, Bruno Contreras‐Moreira, Susanne Dreisigacker, David Edwards, Fernanda G. González, Carlos Guzmán, Tatsuya M. Ikeda, I. Karsaï, Shuhei Nasuda, Curtis Pozniak, R. Prins, Taner Z. Sen, Paula Silva, Hana Šimková, Y Zhang

Bibliographic record

VenueTheoretical and Applied Genetics · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicWheat and Barley Genetics and Pathology
Canadian institutionsUniversity of Saskatchewan
FundersPartnership for Research and Innovation in the Mediterranean AreaEuropean Regional Development FundAustralian Research CouncilBiotechnology and Biological Sciences Research CouncilNational Institute of Food and AgricultureInstituto Nacional de Investigación AgropecuariaInstituto Nacional de Investigacion Agropecuaria, UruguayMinisterio de Ciencia e InnovaciónNational Agriculture and Food Research OrganizationUniversidad Nacional del Centro de la Provincia de Buenos AiresAgencia Nacional de Investigación e InnovaciónKing Abdullah University of Science and TechnologyAgricultural Research ServiceGenome Canada
KeywordsBiologyGeneGenomeGeneticsComputational biologyBiotechnologyTriticeaeNomenclatureGene nomenclatureEcologyTaxonomy (biology)

Abstract

fetched live from OpenAlex

OpenAlex records an abstract for this work, but it could not be fetched just now.

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)0.014
metaresearch head score (Gemma)0.028
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: Not applicable
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.014
Threshold uncertainty score0.072

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.028
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0070.007
Science and technology studies0.0020.003
Scholarly communication0.0040.004
Open science0.0040.002
Research integrity0.0030.008
Insufficient payload (model declined to judge)0.0100.016

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 head0.033
GPT teacher head0.271
Teacher spread0.239 · 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

Citations100
Published2023
Admission routes2
Has abstractyes

Explore more

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