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Record W2096456644 · doi:10.1002/jmor.20192

A review of cetacean lung morphology and mechanics

2013· review· en· W2096456644 on OpenAlexaff
Marina A. Piscitelli, Stephen Raverty, M. A. Lillie, Robert E. Shadwick

Bibliographic record

VenueJournal of Morphology · 2013
Typereview
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsMinistry of AgricultureGovernment of British ColumbiaUniversity of British Columbia
Fundersnot available
KeywordsBiologyMorphology (biology)Evolutionary biologyLungZoologyLinguisticsPhilosophy

Abstract

fetched live from OpenAlex

Cetaceans possess diverse adaptations in respiratory structure and mechanics that are highly specialized for an array of surfacing and diving behaviors. Some of these adaptations and air management strategies are still not completely understood despite over a century of study. We have compiled the historical and contemporary knowledge of cetacean lung anatomy and mechanics in regards to normal lung function during ventilation and air management while diving. New techniques are emerging utilizing pulmonary mechanics to measure lung function in live cetaceans. Given the diversity of respiratory adaptations in cetaceans, interpretations of these results should consider species-specific anatomy, mechanics, and behavior.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.009
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.004
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.003

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 head0.040
GPT teacher head0.309
Teacher spread0.269 · 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
GenreReview

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

Citations93
Published2013
Admission routes1
Has abstractyes

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