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Record W1583638664 · doi:10.1159/000309794

Spatial Summation and the Cortical Magnification of Perimetric Profiles

2010· article· en· W1583638664 on OpenAlexaff
John M. Wild, Joanne M. Wood, John G. Flanagan

Bibliographic record

VenueOphthalmologica · 2010
Typearticle
Languageen
FieldNeuroscience
TopicVisual perception and processing mechanisms
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsSummationMagnificationVisual fieldPhotopic visionScalingVisual cortexHyperacuityAdaptation (eye)Spatial frequencyPerimeterStimulus (psychology)OpticsPhysicsMathematicsRetinaPsychologyNeuroscienceGeometry

Abstract

fetched live from OpenAlex

M-scaling of the conventional spot targets of clinical perimetry at low photopic adaptation levels, such as that of the Octopus automated perimeter, does not result in the expected isosensitive profile using the current equations for humans. This disparity has been attributed to variations in the ganglion cell characteristics across the retina, most notably that of spatial summation. The hypothesis was further investigated by M-scaling the perimetric sensitivity recorded under conditions favouring reduced spatial summation, namely an increased adaptation level and a longer stimulus duration afforded by the Humphrey Field Analyzer. The M-scaled data exhibited a paracentral reduction in sensitivity relative to the theoretical isosensitive profile and an increased sensitivity beyond an eccentricity of 12 degrees. This indicates that for perimetric spot stimuli, the current human M-scaling equations under represent the fovea at the visual cortex. The implications for the design of perimetric routines are discussed.

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)0.000
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 score0.144
Threshold uncertainty score0.672

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.061
GPT teacher head0.329
Teacher spread0.267 · 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
Published2010
Admission routes1
Has abstractyes

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