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Record W2000382808 · doi:10.1242/jeb.064345

SENSORY ORGAN DISCOVERY DEMYSTIFIES RORQUAL WHALE FEEDING

2012· article· en· W2000382808 on OpenAlexaffabout
Cosima S. Porteus

Bibliographic record

VenueJournal of Experimental Biology · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsBaleenWhaleAnatomyFish <Actinopterygii>BiologyChinFishery

Abstract

fetched live from OpenAlex

The rorqual whale family is composed of the largest animals on Earth with a unique way of eating their prey: they dive into aggregations of small crustaceans and fish at great depths and lunge with their mouths wide open, engulfing kilograms of fish in a single mouthful. The volume of each mouthful can be larger than that of their body and the engulfed water is filtered through baleen plates in a matter of seconds, leaving them to consume the food that is left behind. Over the past couple of decades researchers have found many unique morphological features that allow rorqual whales to perform these feats: enormous heads with large flexible jaws, the ability to invert their tongues and incredibly stretchy ventral (along the front of the body) pouches that extend from the chin down to their belly button. Recently, a new sensory organ involved in this fascinating feeding strategy was discovered by a team of North American researchers led by Robert Shadwick from the University of British Columbia, Canada, and they published their findings in Nature.One intriguing anatomical feature of rorqual whales is that the bones in their lower jaws (mandibles) are not fused at the chin but are held together by connective tissue instead. This gives their jaws more flexibility and the ability to rotate outward, enabling the whales to gulp even more water than if their jaws were fused. Dissecting whale carcasses, the team discovered a round, jelly-filled cavity in the connective tissue between the mandibles. A closer look at the tissue with microscopes revealed that the cavity was innervated, and had many papillae (finger-like projections) and nerve endings reminiscent of other sensory organs.To get a better idea of the structure of this organ, they then performed magnetic resonance imaging (MRI) and X-ray computed tomography (CT) scanning on different species of rorqual whales. When they analysed the distribution of bundles of blood vessels and nerves going to the sensory organ, the team discovered an asymmetric distribution – 60% of the nerves and blood vessels originated from the left mandible in fin whales – and they believe that this asymmetry in the innervation is related to the tendency of individual whales to be biased to one side when side gulping or rolling to feed.Another intriguing anatomical feature is a Y-shaped cartilage structure that emerges out of the chin and protrudes along the bony jaws, providing support for the stretchy ventral pouch. Using the same imaging techniques that they had used previously, the team discovered that the sensory organ was in contact with the Y-shaped cartilage. They propose that mechanoreceptors (sensors responding to mechanical stimuli) in the sensory organ located in the mandibles relay information about the configuration of the jaws to the brain in order to co-ordinate the movements of the jaw bones and the soft tissue of the ventral pouch during lunge feeding.This discovery raises interesting questions about the evolution of this organ. Based on its absence in toothed whales, the research team proposes that it evolved either before lunge feeding or along with other specializations associated with lunge feeding and that this organ is an important contributor to this fascinating behaviour.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.034
GPT teacher head0.296
Teacher spread0.262 · 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

Citations0
Published2012
Admission routes2
Has abstractyes

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