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Record W6891784999 · doi:10.48336/1x3a-x190

The retinal topography of the red lionfish (Pterois volitans): towards an understanding of the visual system of a highly invasive species

2023· article· en· W6891784999 on OpenAlexaff

Bibliographic record

VenueMemorial University Research Repository (Memorial University) · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRetinal Development and Disorders
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsRetinaCrepuscularRetinalDorsumRetinal wavesVisual field

Abstract

fetched live from OpenAlex

Retinal specializations provide organisms with the spatial information needed to engage in visually guided behaviours aimed at maximizing fitness; nevertheless, little is known about the retinal topography of crepuscular fish, as most studies address diurnal or deep-sea species. I evaluated the types of photoreceptor and neural cells in the retina of the red lionfish, their distribution in the retinal surface, and their spatial resolving power. Single, double and triple cones are imbedded in a rod-dominated field over the entire inner layer. Single and double cones occur in higher densities towards the dorsal and ventral areas, arranged in a square mosaic pattern all along except in the central region of the retina, where they concur with triple cones. Ganglion and amacrine cells cover the outer layer with higher densities in the ventral-nasal region, a mismatch to single and double cones, and occasionally assemble as glomeruli or striation. Cell distribution and single and double cone arrangements in conjunction with spatial resolving power values suggest vision in P. volitans is adapted for vertically open habitats and performs better in dim-light environments while maintaining a moderate capacity for color vision, which denotes an advantage for predatory capabilities and success as an invasive species.

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 score0.116
Threshold uncertainty score0.875

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0020.001
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 head0.248
Teacher spread0.218 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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