MétaCan
Menu
Back to cohort
Record W3020805387 · doi:10.1093/biosci/biw181

Conserving Transborder Migratory Bats, Preserving Nature's Benefits to Humans: The Lesson from North America's Bird Conservation Treaties

2017· article· en· W3020805387 on OpenAlexaboutno aff
Laura López‐Hoffman, Charles C. Chester, Robert Merideth

Bibliographic record

VenueBioScience · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsnot available
Fundersnot available
KeywordsGeographyConventionTreatyEnvironmental protectionEcologyPolitical scienceBiologyLaw

Abstract

fetched live from OpenAlex

In 2015, Canada, the United States, and Mexico signed a letter of intent to protect the continent's migratory bats. In charting a path for protecting bats, we look to the century of efforts to protect birds. Despite a barrage of obstacles, millions of migratory birds still cross North America each year. One key reason for their survival has been international cooperation. The past year marks the 100th anniversary of the Migratory Bird Treaty between Canada and the United States, as well as the 80th anniversary of a similar agreement between the United States and Mexico. These treaties were based on the practical benefits from migratory birds—values today known as ecosystem services. Migratory bats also provide significant natural benefits to people; a fully fledged international convention on migratory bats would not only protect these benefits but would also celebrate a century of transborder cooperation to conserve migratory species in North America.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.077
Threshold uncertainty score0.153

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0050.007
Scholarly communication0.0050.006
Open science0.0010.003
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0060.001

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 head0.018
GPT teacher head0.245
Teacher spread0.227 · 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 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

Citations5
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueBioScienceSame topicWildlife Ecology and ConservationFrench-language works237,207