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Record W2302300469

Global Research Alliance on Agricultural Greenhouse Gases - benchmark and ensemble crop and grassland model estimates

2016· preprint· en· W2302300469 on OpenAlexaffabout
Renáta Sándor, Fiona Ehrhardt, Bruno Basso, Arti Bathia, Gianni Bellocchi, Lorenzo Brilli, L. M. Cardenas, Massimiliano De Antoni Migliorati, J.D. Bregon, Lucas Doro, Nuala Fitton, Sandro José Giacomini, Peter Grace, Brian Grant, Matthew Tom Harrison, Stephanie Jones, Miko U. F. Kirschbaum, Katja Klumpp, Patricia Laville, Joël Léonard, Mark A. Liebig, Mark Lieffering, Raphaël Martin, Russel McAuliffe, Elizabeth A. Meier, Lutz Merbold, Andrew D. Moore, Vasilis Myrgiotis, Elizabeth Pattey, Sylvie Recous, Suzanne Rolinski, Joanna Sharp, Raia Silvia Massad, Pete Smith, Ward Smith, Val Snow

Bibliographic record

VenueeCite Digital Repository (University of Tasmania) · 2016
Typepreprint
Languageen
FieldAgricultural and Biological Sciences
TopicSoil Carbon and Nitrogen Dynamics
Canadian institutionsInternational Development Research Centre
Fundersnot available
KeywordsEnvironmental scienceGreenhouse gasArable landGrasslandPrimary productionAgricultureVegetation (pathology)Baseline (sea)Agricultural productivitySoil carbonAtmospheric sciencesSoil waterEcosystemAgronomyEcologySoil science
DOInot available

Abstract

fetched live from OpenAlex

CT3 Biogéochimie, physique et écologie des sols EnjS4 Bouclage des cycles N et P et stockage de carbone Typ_Proj_Bourse de thèse/Post-Doc Typ_Proj_Projet ANR CT3 Biogéochimie, physique et écologie des solsEnjS4 Bouclage des cycles N et P et stockage de carboneTyp_Proj_Bourse de thèse/Post-DocTyp_Proj_Projet ANR

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)0.005
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.030
GPT teacher head0.233
Teacher spread0.203 · 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 designSimulation or modeling
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
Published2016
Admission routes2
Has abstractyes

Explore more

Same venueeCite Digital Repository (University of Tasmania)Same topicSoil Carbon and Nitrogen DynamicsFrench-language works237,207