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Record W2161114804 · doi:10.2466/24.22.cp.1.14

Sex Differences and Spatial Separation in the Poggendorff Illusion

2012· article· en· W2161114804 on OpenAlexaff
Stevi-Dawn Knudson, Jennifer Woodland, Alexander E. Wilson

Bibliographic record

VenueComprehensive Psychology · 2012
Typearticle
Languageen
FieldEngineering
TopicSpatial Cognition and Navigation
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsOblique caseIllusionIntersection (aeronautics)Line (geometry)PsychologyVertical axisGeometryFocus (optics)OpticsCognitive psychologyMathematicsPhysicsGeographyCartography

Abstract

fetched live from OpenAlex

This study examined the responses of 40 undergraduate women and 40 men to two Poggendorff figures, a traditional figure with the right oblique line omitted and a modified variant with the left vertical line and the right oblique line absent. Participants placed a dot on the right vertical line where the oblique line, if extended, would intersect the right vertical line. The results showed that women displayed larger illusions than men on both figures, consistent with past findings. Finding a sex difference with the modified variant did not support the suggestion that the intersection between the oblique and vertical lines is responsible for such differences. The effects of spatial separation and size of acute angle were similar for both versions of the illusion. The effects of spatial separation were inconsistent with an explanation of the illusion based on depth cues and it was suggested that an explanation of the Poggendorff illusion should focus on processing between the vertical lines.

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)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.045
GPT teacher head0.326
Teacher spread0.281 · 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 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
Published2012
Admission routes1
Has abstractyes

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