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Record W6950004806 · doi:10.5281/zenodo.4342880

Rousettus leschenaultii Desmarest 1820

2013· article· en· W6950004806 on OpenAlexaff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicAmphibian and Reptile Biology
Canadian institutionsEnvironment and Climate Change Canada
Fundersnot available
KeywordsCaveDistribution (mathematics)Southeast asia

Abstract

fetched live from OpenAlex

Rousettus leschenaultii Desmarest, 1820 Leschenault’s rousette Pteropus leschenaulti Desmarest, 1820: 110; Pondicherry, India. Distribution Sri Lanka, India, Bangladesh, Bhutan, Pakistan, Nepal; S China; Myanmar, Thailand, Lao PDR, Vietnam, and ranging into Indonesia (Sumatra, Java, Bali, and the Mentawai islands). Distribution in Lao PDR (Fig. 3): Bolikhamxai Province: Ban Van Hom (Ban Vanhom) (Philips, 1967); Champasak Province: Ban Taong, Xe Pian NBCA (Robinson, 1998); Nong Luang (Nong Louang) (HNHM collection); Khammouan Province: Phon Tiou (Ban Phontiou) (Philips, 1967); Tam Jungvung Cave (Tham Chungvung) (Robinson and Webber, 2000); Louangnamtha Province: Tham Pasatthia 3 (HI collection); Vientiane Province: Nam Ngum (Bergmans, 1995); Xaignabouli Province: [Pha Deng] (Bergmans, 1995); Xekong Province: [Sekong Town (Xekong)] (Bergmans 1995).

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)0.000
metaresearch head score (Gemma)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.002

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 head0.021
GPT teacher head0.210
Teacher spread0.189 · 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
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

Citations0
Published2013
Admission routes1
Has abstractyes

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