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Record W2172312222 · doi:10.1644/06-mamm-r-063r.1

Mammal Tracks and Sign —A Guide to North American Species

2006· article· en· W2172312222 on OpenAlexaff
David F. Hatler

Bibliographic record

VenueJournal of Mammalogy · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsPacific Insight Electronics (Canada)
Fundersnot available
KeywordsMammalSign (mathematics)GeographyEcologyZoologyBiologyMathematics

Abstract

fetched live from OpenAlex

M Elbroch. 2003. Mammal Tracks and Sign—A Guide to North American Species. Stackpole Books, Mechanicsburg, Pennsylvania, 779 pp. ISBN 0-8117-2626-6, price (paper) $44.95. A sticker on the cover indicates that this book has been a winner of the National Outdoor Book Award, and it is easy to see why. With more than 1,000 high-quality color photographs, another 300+ well-drawn illustrations, and numerous detailed descriptions with painstaking measurements, it is unmatched in encyclopedic breadth by anything that has come before. That will be positive for some potential users, but a distinct liability for others. Although built like a field guide, with heavy paper and a tough cover, at 14 × 21 ×4 cm it is 2.5 times the volume of Murie (1954) original in the Peterson field guide series and, at 1.25 kg, is 3.5 times heavier. In practical terms, most users will probably want to take mammal “sign” to the book rather than the book to sign. With the advent and proliferation of compact digital cameras, that may now be easier to accomplish than it used to be. In a lengthy introduction and in Chapter 1 ( Getting Started ), the author makes clear his passion for tracking and offers a variety of perspectives on the physical, mental, and sometimes metaphysical aspects involved. Although he mentions and strongly advocates use of tracking in scientific study, examples provided are mostly from …

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.450

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 head0.006
GPT teacher head0.211
Teacher spread0.205 · 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 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

Citations69
Published2006
Admission routes1
Has abstractyes

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