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Pattern-Evoked Potential Latencies From Central and Peripheral Visual Fields

2000· article· en· W2062643273 on OpenAlexaff
Daniel Jones, Warren T. Blume

Bibliographic record

VenueJournal of Clinical Neurophysiology · 2000
Typearticle
Languageen
FieldNeuroscience
TopicVisual perception and processing mechanisms
Canadian institutionsWestern University
Fundersnot available
KeywordsPeripheralVisual fieldEvoked potentialNeuroscienceStimulationVisual evoked potentialsVisual cortexLatency (audio)Peripheral visionVisual N1AudiologyMedicineVisual perceptionPsychologyPhysicsComputer scienceOpticsPerceptionInternal medicineTelecommunications

Abstract

fetched live from OpenAlex

Median P100 and N70 latencies for peripheral field (>8 degrees) TV-generated pattern visual-evoked potentials were 6 and 8 milliseconds less than for central field patterns in subjects with normal pattern visual-evoked potentials. These differences held for patient subgroups with P100 latency maxima from 140 to 100 milliseconds, and for left and right eye data separately compiled. Latencies for central field stimulation exceeded those for peripheral field stimulation in 233 (85%) of 274 eyes for the N70 potential and in 210 (77%) of 274 eyes for the P100 potential. Such data suggest that the faster conducting peripheral visual system, conveying location and motion information, prepares the occipital cortex for the later arriving central data conveying more intricate details.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.892
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.062
GPT teacher head0.372
Teacher spread0.311 · 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.

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

Citations2
Published2000
Admission routes1
Has abstractyes

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