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Anaconda

2020· book· en· W4233192798 on OpenAlexaboutno aff
Jesús A. Rivas

Bibliographic record

VenueOxford University Press eBooks · 2020
Typebook
Languageen
FieldEnvironmental Science
TopicAmphibian and Reptile Biology
Canadian institutionsnot available
Fundersnot available
KeywordsStress (linguistics)Visual artsStorytellingArtQuarter (Canadian coin)PhotographyArt historyHistoryLiteraturePhilosophyLinguisticsArchaeologyNarrative

Abstract

fetched live from OpenAlex

Written by Jesús Rivas, the undisputed expert on the biology of anacondas, this is the first authoritative book on the biology of the green anaconda, the world’s largest snake. Rivas describes his experiences over a quarter of a century exploring the secret life of these fantastic snakes, including their diet, movement patterns, life and tribulations, survival, behavior, and fascinating reproductive life. But more than just presenting facts about anacondas, Rivas tells his story about studying them in the field. Ultimately, his love for anacondas and his unorthodox approach give his voice a unique accent that makes this book stand out among other books of its kind. The rich photography and its storytelling approach make this an enjoyable and thoroughly readable book that can sit as comfortably on a coffee table as in the bookshelves of advanced scholars.

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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.149
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.1490.069

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 head0.014
GPT teacher head0.180
Teacher spread0.165 · 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
GenreOther

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

Citations11
Published2020
Admission routes1
Has abstractyes

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Same venueOxford University Press eBooksSame topicAmphibian and Reptile BiologyFrench-language works237,207