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Record W3015027376 · doi:10.1016/j.biocon.2020.108571

Impacts of the coronavirus pandemic on biodiversity conservation

2020· editorial· en· W3015027376 on OpenAlexaff
Richard T. Corlett, Richard B. Primack, Vincent Devictor, Bea Maas, Varun R. Goswami, Amanda E. Bates, Lian Pin Koh, Tracey J. Regan, Rafael Loyola, Robin J. Pakeman, Graeme S. Cumming, Anna M. Pidgeon, David Johns, Robin Roth

Bibliographic record

VenueBiological Conservation · 2020
Typeeditorial
Languageen
FieldMedicine
TopicZoonotic diseases and public health
Canadian institutionsUniversity of GuelphMemorial University of Newfoundland
Fundersnot available
KeywordsPandemicBiodiversityWildlifeSustainabilityPublic relationsConvention on Biological DiversityEnvironmental ethicsCoronavirus disease 2019 (COVID-19)Political scienceEnvironmental planningEnvironmental resource managementGeographyEcologyInfectious disease (medical specialty)BiologyMedicine

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)0.015
metaresearch head score (Gemma)0.043
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.038
Threshold uncertainty score0.089

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.043
Meta-epidemiology (narrow)0.0060.002
Meta-epidemiology (broad)0.0060.004
Bibliometrics0.0050.003
Science and technology studies0.0050.004
Scholarly communication0.0120.008
Open science0.0060.004
Research integrity0.0380.032
Insufficient payload (model declined to judge)0.0260.015

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 head0.113
GPT teacher head0.337
Teacher spread0.224 · 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 designNot applicable
Domainnot available
GenreEditorial

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

Citations384
Published2020
Admission routes1
Has abstractno

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