The effect of distinctive parts on recognition of depth-rotated objects by pigeons (Columba livia) and humans.
Bibliographic record
Abstract
To explore whether effects observed in human object recognition represent fundamental properties of visual perception that are general across species, the authors trained pigeons (Columba livia) and humans to discriminate between pictures of 3-dimensional objects that differed in shape. Novel pictures of the depth-rotated objects were then tested for recognition. Across conditions, the object pairs contained either 0, 1, 3, or 5 distinctive parts. Pigeons showed viewpoint dependence in all object-part conditions, and their performance declined systematically with degree of rotation from the nearest training view. Humans showed viewpoint invariance for novel rotations between the training views but viewpoint dependence for novel rotations outside the training views. For humans, but not pigeons, viewpoint dependence was weakest in the 1-part condition. The authors discuss the results in terms of structural and multiple-view models of object recognition.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".