Independent representation of parts and the relations between them: Evidence from integrative agnosia.
Bibliographic record
Abstract
Whether objects are represented as a collection of parts whose relations are coded independently remains a topic of ongoing discussion among theorists in the domain of shape perception. S. M., an individual with integrative agnosia, and neurologically intact ("normal") individuals learned initially to identify 4 target objects constructed of 2 simple volumetric parts. At test, the targets were mixed with distractors, some of which could be discriminated from the targets on the basis of a mismatching part, whereas the rest could be discriminated only on the basis of the altered spatial arrangements of parts. S. M. learned to identify the target objects, although at a rate slower than that of the normal participants. At test, he correctly rejected distractors on the basis of mismatching parts but was profoundly impaired at rejecting distractors made of the same local components but with mismatching spatial arrangements. These results suggest that encoding the spatial arrangements of parts of an object requires a mechanism that is different from that required for encoding the shape of individual parts, with the former selectively compromised in integrative agnosia.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".