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Record W2029753119 · doi:10.1167/5.8.185

Labelled lines for phase?

2010· article· en· W2029753119 on OpenAlexaff
Pi‐Chun Huang, Robert F. Hess, Frederick A. A. Kingdom

Bibliographic record

VenueJournal of Vision · 2010
Typearticle
Languageen
FieldNeuroscience
TopicVisual perception and processing mechanisms
Canadian institutionsMcGill University
Fundersnot available
KeywordsStimulus (psychology)Phase (matter)SinePhysicsPsychophysicsMathematicsPattern recognition (psychology)Computer scienceArtificial intelligencePsychologyPerceptionGeometryNeuroscience

Abstract

fetched live from OpenAlex

Purpose. There is psychophysical support for a phase model of visual processing involving four channels, each optimally sensitive to one of the following four phase relations; + cosine, − cosine, +sine and − sine. Neurophysiology suggests either an even distribution of neuronal phase responses or else a sine/cosine phase dichotomy that is dependent on spatial bandwidth. We investigated whether there were labelled lines for phase; this can be thought of as testing a strong version of the four channel phase model in which each of the above phases can be discriminated at threshold. Methods. Our stimulus comprised Gaussian weighted (space and time) patches of either Gabor or edge/bar stimuli for which we measure simultaneously detection and phase identification to determine if phase identification can be accomplished at detection threshold (hence labelled lines). We used two bandwidths of Gabor and varied both absolute and relative phase. Results. Subjects could not reliably discriminate at threshold Gabors of even symmetry from Gabors of odd symmetry nor could they discriminate bar from edge stimuli. Conclusion. While there may be labelled lines for polarity there are not labelled lines for bars vs edges. The smallest discriminable step we can reliably make across the phase spectrum at threshold is 180°.

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)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.046
Threshold uncertainty score0.155

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0460.018

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 head0.067
GPT teacher head0.424
Teacher spread0.357 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations1
Published2010
Admission routes1
Has abstractyes

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