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Record W2195716475 · doi:10.1644/05-mamm-r-332r1.1

Noninvasive Study of Mammalian Populations

2006· article· en· W2195716475 on OpenAlexaff
Jeff W. Higdon

Bibliographic record

VenueJournal of Mammalogy · 2006
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicIdentification and Quantification in Food
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsBiologyZoologyEvolutionary biologyGeography

Abstract

fetched live from OpenAlex

W. E. Evans, A. V. Yablokov. 2004. Noninvasive Study of Mammalian Populations. Pensoft Publishers, Sofia, Bulgaria, 142 pp., bibliography. ISBN 954-642-204-5, price (hardbound) $37.80. Improving knowledge on threatened species must be done in a manner that does not compromise individuals, and hence populations. The use of noninvasive techniques has great potential in the study and conservation of endangered species. With this end in mind, Evans and Yablokov have written Noninvasive Study of Mammalian Populations . The book is mostly an English-language expansion and revision of their 1983 Russian monograph on cetacean color patterns (Evans and Yablokov 1983). Their approach was motivated by a need to develop less intensive, and nonlethal, ways to study endangered species. The authors have researched cetacean color pattern since the early 1970s. However, noninvasive identification techniques were certainly not new at the time, because cattle breeders have used nose prints to identify individual bulls and their …

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 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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.538
Threshold uncertainty score0.249

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 head0.029
GPT teacher head0.292
Teacher spread0.263 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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
Published2006
Admission routes1
Has abstractyes

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