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Record W2031016961 · doi:10.1068/p3033

Cavanagh and Leclerc Shape-From-Shadow Pictures: Do Line Versions Fail Because of the Polarity of the Regions or the Contour?

2000· article· en· W2031016961 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePerception · 2000
Typearticle
Languageen
FieldNeuroscience
TopicVisual perception and processing mechanisms
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsShadow (psychology)Line (geometry)Polarity (international relations)PerceptionArtificial intelligenceReferentFilling-inComputer visionLine drawingsOpticsPhysicsGeometryComputer sciencePsychologyMathematicsPhilosophy

Abstract

fetched live from OpenAlex

Shape-from-shadow perception fails when the contour bordering a shadowed area is reduced to a black line, and the shadow area becomes white. It might be that the polarity of the shadowed and illuminated areas has to be from dark on the shadowed side to light on the illuminated side for successful perception. Or it may be that the line, which has two contours, has one too many for shape-from-shadow processing. Alternatively, the problem might be that one of the contours of the line is incorrectly polarised. To test these explanations, three shape-from-shadow figures were prepared, each depicting the same referent--an elderly person. All three figures had two correctly polarised areas. One figure had a correctly polarised contour at the border between the areas. One had two correctly polarised contours. The other had one correctly polarised contour and one incorrectly polarised contour. The referent of the figure with one incorrectly polarised contour was the one difficult to make out. The result has implications for several theories, including an account of a demonstration by Hering involving penumbra.

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.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.863
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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.067
GPT teacher head0.309
Teacher spread0.241 · 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