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Record W2980425370

Trade and conservation efforts involving the Sumatran Laughingthrush Garrulax bicolor in Indonesia

2018· article· en· W2980425370 on OpenAlex
Chris R. Shepherd, Lalita Gomez

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicLivestock and Poultry Management
Canadian institutionsWildlife Conservation Society Canada
Fundersnot available
KeywordsThreatened speciesIUCN Red ListEndangered speciesIndonesianGeographyEcologyEnforcementAgroforestryBiologyHabitat
DOInot available

Abstract

fetched live from OpenAlex

In 2018, the Indonesian Government provided legal protection for the Sumatran Laughingthrush Garrulax bicolor. This species, endemic to the island of Sumatra, is now restricted to a few submontane and montane forests on the north and south of the island. Heavily trapped for the Indonesian songbird trade, populations are in serious decline. Calls to provide full protection for this species were made close to 15 years ago, and since that time, the Sumatran Laughingthrush has become very rare and categorised as Endangered by the IUCN Red List of Threatened Species. While ex-situ conservation breeding programmes may help ensure this species does not go extinct, its continued survival in the wild will depend very much on effective law enforcement in Indonesia.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.091
Threshold uncertainty score0.257

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.022
GPT teacher head0.217
Teacher spread0.196 · 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

Quick stats

Citations3
Published2018
Admission routes1
Has abstractyes

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