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Record W2297507614 · doi:10.1002/jmor.20510

Baleen wear reveals intraoral water flow patterns of mysticete filter feeding

2016· article· en· W2297507614 on OpenAlexaff
Alexander Werth, Janice M. Straley, Robert E. Shadwick

Bibliographic record

VenueJournal of Morphology · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsUniversity of British Columbia
FundersNaturalis Biodiversity Center
KeywordsBaleenWhaleBiologyAnatomyFishery

Abstract

fetched live from OpenAlex

A survey of macroscopic and microscopic wear patterns in the baleen of eight whale species (Cetacea: Mysticeti) discloses structural, functional, and life history properties of this neomorphic keratinous tissue, including evidence of intraoral water flow patterns involved in filter feeding. All baleen demonstrates wear, particularly on its medial and ventral edges, as flat outer layers of cortical keratin erode to reveal horn tubes, also of keratin, which emerge as hair-like fringes. This study quantified five additional categories of specific wear: pitting of plates, scratching of plates, scuffing of fringes, shortening of fringes, and reorientation of fringes (including fringes directed between plates to the exterior of the mouth). Blue whale baleen showed the most pitting and sei whale baleen the most scratching; gray whale baleen had the most fringe wear. The location of worn baleen within the mouth suggests that direct contact with the tongue is not responsible for most wear, and that flowing water as well as abrasive prey or sediment carried by the flowing water likely causes pitting and scratching of plates as well as fringe fraying, scuffing, shortening, and reorientation. Baleen also has elevated vertical and horizontal ridges that are unrelated to wear; these are probably related to growth and may allow for age determination.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.018
GPT teacher head0.232
Teacher spread0.214 · 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

Citations26
Published2016
Admission routes1
Has abstractyes

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