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Record W3089772025 · doi:10.5751/ace-01719-160101

Raptor resource use in agroecosystems: cover crops and definitions of availability matter

2021· article· en· W3089772025 on OpenAlexvenueno aff
Megan E. Zagorski, Robert K. Swihart

Bibliographic record

VenueAvian Conservation and Ecology · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture and Biological Studies
Canadian institutionsnot available
FundersNatural Resources Conservation ServiceNational Institute of Food and AgricultureIndiana State Department of AgriculturePurdue UniversityU.S. Department of Agriculture
KeywordsAgroecosystemAgroforestryEcologyCover (algebra)Resource (disambiguation)GeographyEnvironmental scienceAgricultureBiology

Abstract

fetched live from OpenAlex

Zagorski, M. E. and R. K. Swihart. 2021. Raptor resource use in agroecosystems: cover crops and definitions of availability matter. Avian Conservation and Ecology 16(1):1. https://doi.org/10.5751/ACE-01719-160101

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)0.002
metaresearch head score (Gemma)0.005
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 score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0000.002
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.041
GPT teacher head0.199
Teacher spread0.159 · 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

Citations7
Published2021
Admission routes1
Has abstractyes

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