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Record W2058223517

Annual Wheat Newsletter. Volume 54

2008· article· en· W2058223517 on OpenAlexfundno aff
W. J. Raupp

Bibliographic record

VenueK-State Research Exchange (Kansas State University) · 2008
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicWheat and Barley Genetics and Pathology
Canadian institutionsnot available
FundersAgricultural Research ServicePartenariat Canadien Contre Le CancerShandong Academy of Agricultural SciencesNational Institutes of HealthInstituto Nacional de Investigación AgropecuariaUniversidad de la República UruguayChinese Academy of Agricultural SciencesKansas Wheat CommissionArcadia FundIndian Council of Agricultural ResearchStrongWashington Grain CommissionMcMaster UniversityNational Institute of Food and AgricultureOregon State UniversityBundesministerium für Ernährung und LandwirtschaftMontana State UniversityNational Research Council CanadaInstituto Nacional de Investigación y Tecnología Agraria y AlimentariaClemson UniversityPurdue UniversityMcKnight FoundationUniversity of California, RiversideSouth Dakota State UniversityDepartment of Biotechnology, Ministry of Science and Technology, IndiaNational Science FoundationUniversity of MinnesotaUnited States Agency for International DevelopmentICAR - National Agricultural Science FundU.S. Department of AgricultureBiotechnology Industry Research Assistance CouncilNorth Dakota State UniversityWashington State University
KeywordsVolume (thermodynamics)Environmental scienceGeologyRemote sensingPhysics
DOInot available

Abstract

fetched live from OpenAlex

The Annual Wheat Newsletter is edited by W.J. Raupp and published by the Wheat Genetic and Genomic Resources Center at Kansas State University. The scope of the Newsletter includes current project activities, cultivar releases, special reports, and publications of wheat researchers worldwide. The Newsletter annually has over 100 contributors from more than 30 countries.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.614
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.063
GPT teacher head0.254
Teacher spread0.191 · 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.

Study designNot applicable
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

Citations0
Published2008
Admission routes1
Has abstractyes

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