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Record W2104004533 · doi:10.1098/rspb.2006.0246

Communication using eye roll reflective signalling

2007· article· en· W2104004533 on OpenAlexafffund
Iñigo Novales Flamarique, Gordon Mueller, Christiana L. Cheng, Chester R. Figiel

Bibliographic record

VenueProceedings of the Royal Society B Biological Sciences · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRetinal Development and Disorders
Canadian institutionsSimon Fraser University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAdaptation (eye)Contrast (vision)Chromatic scaleRetinaFlash (photography)BiologySIGNAL (programming language)SuckerOpticsPhysicsAnatomyNeuroscienceComputer science

Abstract

fetched live from OpenAlex

Body reflections in the ultraviolet (UV) are a common occurrence in nature. Despite the abundance of such signals and the presence of UV cones in the retinas of many vertebrates, the function of UV cones in the majority of taxa remains unclear. Here, we report on an unusual communication system in the razorback sucker, Xyrauchen texanus, that involves flash signals produced by quick eye rolls. Behavioural experiments and field observations indicate that this form of communication is used to signal territorial presence between males. The flash signal shows highest contrast in the UV region of the visual spectrum (lambdamax approximately 380 nm), corresponding to the maximum wavelength of absorption of the UV cone mechanism in suckers. Furthermore, these cones are restricted to the dorsal retina of the animal and the upwelling light background is such that their relative sensitivity would be enhanced by chromatic adaptation of the other cone mechanisms. Thus, the UV cones in the sucker have optimal characteristics (both in terms of absorbance and retinal topography) to constitute the main detectors of the flash signal. Our findings provide the first ecological evidence for restricted distribution of UV cones in the retina of a vertebrate.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.111
Threshold uncertainty score0.286

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.030
GPT teacher head0.300
Teacher spread0.270 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations13
Published2007
Admission routes2
Has abstractyes

Explore more

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