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Record W3010287583 · doi:10.1111/icad.12408

Interpreting insect declines: seven challenges and a way forward

2020· article· en· W3010287583 on OpenAlexaff
Raphaël K. Didham, Yves Basset, C. Matilda Collins, Simon R. Leather, Nick A. Littlewood, Myles H. M. Menz, Jörg Müller, Laurence Packer, Manu E. Saunders, Karsten Schönrogge, Alan J. A. Stewart, Stephen P. Yanoviak, Christopher Hassall

Bibliographic record

VenueInsect Conservation and Diversity · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicSpecies Distribution and Climate Change
Canadian institutionsYork University
FundersH2020 Marie Skłodowska-Curie ActionsUniversity of New EnglandNatural Environment Research CouncilEuropean CommissionSight Research UKUK Research and Innovation
KeywordsRepresentativeness heuristicPopulationCitizen scienceClimate changeScrutinyBaseline (sea)EcologyProspectusInferenceData scienceEnvironmental resource managementBiologyComputer sciencePolitical scienceBusinessArtificial intelligenceEconomicsStatistics

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)0.226
metaresearch head score (Gemma)0.324
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.226
Threshold uncertainty score0.954

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2260.324
Meta-epidemiology (narrow)0.0040.003
Meta-epidemiology (broad)0.0070.004
Bibliometrics0.0080.006
Science and technology studies0.0070.030
Scholarly communication0.0230.042
Open science0.0110.017
Research integrity0.0260.040
Insufficient payload (model declined to judge)0.0100.005

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 head0.094
GPT teacher head0.236
Teacher spread0.142 · 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.

Study designTheoretical or conceptual
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

Citations438
Published2020
Admission routes1
Has abstractyes

Explore more

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