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Record W2322155601 · doi:10.1167/iovs.14-15644

Photoreceptor Regulation of Spatial Visual Behavior

2015· article· en· W2322155601 on OpenAlexaff
Nazia M. Alam, Cara M. Altimus, Robert M. Douglas, Samer Hattar, Glen T. Prusky

Bibliographic record

VenueInvestigative Ophthalmology & Visual Science · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRetinal Development and Disorders
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsLuminanceContrast (vision)Visual phototransductionOpticsCone (formal languages)PhysicsRetinaRodGratingVisual systemNeuroscienceBiologyComputer scienceMedicine

Abstract

fetched live from OpenAlex

PURPOSE: To better understand how photoreceptors and their circuits support luminance-dependent spatial visual behavior. METHODS: Grating thresholds for optokinetic tracking were measured under defined luminance conditions in mice with genetic alterations of photoreceptor activity. RESULTS: The luminance conditions that enable cone- and rod-mediated behavior, and the luminance range over which rod and cone functions overlap, were characterized. The AII amacrine pathway was found to support low-resolution and high-contrast function, with the rod-cone pathway supporting high-resolution and low-contrast function. Rods alone were also shown to be capable of driving cone-like spatial visual function, but only when cones were genetically maintained in a physiological dark state. CONCLUSIONS: The study defined how luminance signals drive rod- and cone-mediated spatial visual behavior and revealed new and unexpected contributions for rods that depend on an interaction between cone and rod systems.

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)0.001
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 score0.983

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.003
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 head0.034
GPT teacher head0.332
Teacher spread0.298 · 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

Citations27
Published2015
Admission routes1
Has abstractyes

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