MétaCan
Menu
Back to cohort
Record W4395066653 · doi:10.1016/j.agee.2024.109036

Pollination deficits and their relation with insect pollinator visitation are cultivar-dependent in an entomophilous crop

2024· article· en· W4395066653 on OpenAlexafffund
Maxime Eeraerts, Stan Chabert, Lisa W. DeVetter, Péter Batáry, John J. Ternest, Kris Verheyen, Kyle Bobiwash, Kayla Brouwer, Daniel Garcı́a, G.A. de Groot, Jason Gibbs, Lauren Goldstein, David Kleijn, Andony Melathopoulos, Sharron Z. Miller, Marcos Miñarro, Ana Montero‐Castaño, Charlie Nicholson, Jackie Perkins, Nigel E. Raıne, Sujaya Rao, James R. Reilly, Taylor H. Ricketts, Emma Rogers, Rufus Isaacs

Bibliographic record

VenueAgriculture Ecosystems & Environment · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsUniversity of GuelphUniversity of Manitoba
FundersNational Research, Development and Innovation OfficeAgencia Estatal de InvestigaciónNemzeti Kutatási Fejlesztési és Innovációs HivatalUniversity of GuelphFonds Wetenschappelijk OnderzoekOntario Ministry of Agriculture, Food and Rural AffairsWeston Family FoundationOregon Blueberry CommissionMinistry of Agriculture, Food and Rural AffairsBelgian American Educational FoundationNational Institute of Food and AgricultureCanada First Research Excellence FundNatural Sciences and Engineering Research Council of CanadaMinisterie van Landbouw, Natuur en VoedselkwaliteitU.S. Department of AgricultureNational Science Foundation
KeywordsPollinationPollinatorBiologyCultivarCropAgronomyHand-pollinationOpen pollinationPollenBotany

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.019
GPT teacher head0.181
Teacher spread0.162 · 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 designObservational
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

Citations20
Published2024
Admission routes2
Has abstractno

Explore more

Same venueAgriculture Ecosystems & EnvironmentSame topicPlant and animal studiesFrench-language works237,207