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Record W4390046068 · doi:10.1126/science.adn3245

A landmark environmental law looks ahead

2023· article· en· W4390046068 on OpenAlexaff
Robert L. Fischman, J. B. Ruhl, Brenna R. Forester, Tanya M. Lama, Marty Kardos, Grethel Aguilar Rojas, Nicholas A. Robinson, Patrick D. Shirey, Gary A. Lamberti, Amy W. Ando, Stephen R. Palumbi, Michael W. Wara, Mark W. Schwartz, Matthew A. Williamson, Tanya Berger‐Wolf, Sara Beery, David Rolnick, Justin Kitzes, David Thau, Devis Tuia, Daniel I. Rubenstein, Caleb R. Hickman, Julie Thorstenson, Gregory E. Kaebnick, James P. Collins, Athmeya Jayaram, Thomas Deleuil, Ying Zhao

Bibliographic record

VenueScience · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicConservation, Ecology, Wildlife Education
Canadian institutionsMcGill UniversityMila - Quebec Artificial Intelligence Institute
Fundersnot available
KeywordsEndangered speciesLoomingEnvironmental lawPolitical scienceEnvironmental ethicsLandmarkGeographyLawEcologyHabitatBiologyCartographyPsychology

Abstract

fetched live from OpenAlex

In late December 1973, the United States enacted what some would come to call “the pitbull of environmental laws.” In the 50 years since, the formidable regulatory teeth of the Endangered Species Act (ESA) have been credited with considerable successes, obliging agencies to draw upon the best available science to protect species and habitats. Yet human pressures continue to push the planet toward extinctions on a massive scale. With that prospect looming, and with scientific understanding ever changing, Science invited experts to discuss how the ESA has evolved and what its future might hold. —Brad Wible

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)0.003
metaresearch head score (Gemma)0.011
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: none
Teacher disagreement score0.030
Threshold uncertainty score0.068

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.006
Scholarly communication0.0090.008
Open science0.0010.004
Research integrity0.0110.014
Insufficient payload (model declined to judge)0.0200.005

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 head0.013
GPT teacher head0.248
Teacher spread0.235 · 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

Citations6
Published2023
Admission routes1
Has abstractyes

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