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Mammal Tracks and Sign of the Northeast

2004· article· en· W2349264434 on OpenAlexaff
Serge Larivière

Bibliographic record

VenueJournal of Mammalogy · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and biodiversity studies
Canadian institutionsCentre de Géomatique du Québec
Fundersnot available
KeywordsMammalSign (mathematics)GeographyPaleontologyBiologyMathematics

Abstract

fetched live from OpenAlex

Animal tracks are always fascinating, and being able to identify tracks and sign from various mammals is always useful for biologists and scientists. Mammal Tracks and Sign of the Northeast offers a drawing-based field guide to facilitate this task. The presentation of the book is adequate, and drawings of animals accompany most chapters. Moreover, a dichotomous key to tracks is provided, and that is an unusual and appreciated contribution in tracking books. These qualities, however, are offset by several flaws. Most notably is one difficulty associated with using drawings instead of photographs to illustrate tracks and sign. In many cases, drawings do little to help understand the real aspects of animal feet, tracks, or scat. For example, many drawings of scats depict side views, providing little help to clearly visualize snowshoe hare (p. 25) or beaver pellets (p. 39), muskrat droppings (p. 45), or bear scat (p. 68). Scat are important animal signs, and without a clear guide, a strong component of identifying animal signs is unavailable.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.026
Threshold uncertainty score0.088

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0260.005

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 head0.007
GPT teacher head0.181
Teacher spread0.174 · 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 designObservational
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
Published2004
Admission routes1
Has abstractyes

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