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Record W2798312162 · doi:10.1017/cbo9780511606595

Darwin's Fishes

2004· book· en· W2798312162 on OpenAlexaff
Daniel Pauly

Bibliographic record

VenueCambridge University Press eBooks · 2004
Typebook
Languageen
FieldEnvironmental Science
TopicAquatic Ecosystems and Biodiversity
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsDarwin (ADL)IchthyologyContext (archaeology)Charles darwinEncyclopediaEvolutionary ecologyFish <Actinopterygii>EcologyBiologyEnvironmental ethicsGenealogyZoologyDarwinismEvolutionary biologyPhilosophyHistoryFisheryComputer sciencePaleontology

Abstract

fetched live from OpenAlex

In Darwin's Fishes, Daniel Pauly presents an encyclopaedia of ichthyology, ecology and evolution, based upon everything that Charles Darwin ever wrote about fish. Entries are arranged alphabetically and can be about, for example, a particular fish taxon, an anatomical part, a chemical substance, a scientist, a place, or an evolutionary or ecological concept. The reader can start wherever they like and are then led by a series of cross-references on a fascinating voyage of interconnected entries, each indirectly or directly connected with original writings from Darwin himself. Along the way, the reader is offered interpretation of the historical material put in the context of both Darwin's time and that of contemporary biology and ecology. This book is intended for anyone interested in fishes, the work of Charles Darwin, evolutionary biology and ecology, and natural history in general.

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 score0.021
Threshold uncertainty score0.071

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.003
Scholarly communication0.0030.003
Open science0.0000.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0210.010

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 head0.013
GPT teacher head0.164
Teacher spread0.150 · 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

Citations36
Published2004
Admission routes1
Has abstractyes

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