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Record W2051322397 · doi:10.1159/000113636

The Contribution of Ultraviolet and Short-Wavelength Sensitive Cone Mechanisms to Color Vision in Rainbow Trout

2008· article· en· W2051322397 on OpenAlexaff
David J. Coughlin, Craig W. Hawryshyn

Bibliographic record

VenueBrain Behavior and Evolution · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicFish biology, ecology, and behavior
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsSpectral sensitivityColor visionTectumUltravioletWavelengthContrast (vision)Rainbow troutOpticsNeurosciencePhysicsBiologyCentral nervous systemMidbrainFish <Actinopterygii>

Abstract

fetched live from OpenAlex

Color vision in rainbow trout was studied by characterizing the spectral sensitivity of single units in three areas of visual processing: optic nerve; optic tectum; and torus semicircularis. Sensitivity to medium wavelength stimuli was a common feature of all single units examined. Additionally, long wavelength sensitivity was found in all units that were not medium wavelength-only or monophasic. Ultraviolet and short-wavelength sensitivity was common in small, juvenile trout, with ultraviolet sensitive units found in the optic nerve and torus, and short wavelength sensitivity found in the optic nerve and tectum. The shorter wavelength inputs were excitatory and, if found in the same unit, synergistic. The most common type of unit in the trout tectum and optic nerve is trichromatic, with ON inputs from the long and short cone mechanisms and an OFF input from the medium mechanism. In contrast, goldfish color vision is dominated by L and M opponent units without S input. The segregation of ultraviolet sensitivity in the torus but not in the tectum relates to functional differences of these two areas. While the tectum serves the function of wavelength discrimination, ultraviolet inputs to the torus may contribute to prey detection and orientation.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.011
GPT teacher head0.245
Teacher spread0.234 · 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

Citations34
Published2008
Admission routes1
Has abstractyes

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