Bibliographic record
Abstract
Purpose: Previous studies indicate that by two months of age, infants integrate one- (1D) and two-dimensional (2D) motion signals (Dobkins, Lewis & Fine, 2006). Here, we investigated whether infants are sensitive to depth-ordering (occlusion) cues that determine whether 2D features are seen as intrinsic or extrinsic to moving 1D features. Methods: Modeled after the barber-diamond (BD) stimulus of Duncan, Albright & Stoner (2000), our BD stimulus consisted of vertically moving gratings (0.8 cpd, 8 Hz) presented within 83 diamond-shaped apertures (3 × 3 deg), evenly spaced across the display. Two occluding white bars (3.0 by 0.4 deg) abutted each BD on opposite sides. The two other sides were framed by a black background. We predicted that 2D terminators abutting the occluders would appear as extrinsic to the moving gratings, while 2D terminators along the two (unoccluded) sides would appear as intrinsic. Using a directional (left vs. right) eye movement (DEM) technique, we asked whether infants distinguished between the motion of intrinsic and extrinsic terminators, which moved up/right (45 deg) and up/left (135 deg), respectively (or vice versa). Performance (where 50% = chance) from the BD condition was compared to that from an Equivalent Direction (ED) condition, which consisted of diamond-shaped apertures containing unambiguous grating motion at 45 or 135 deg. For each infant, a BD index (BDI) was calculated as: (DEM performance on the BD condition-50%)/(DEM performance on the ED condition-50%). BDI values greater than 0 indicate a BD effect. Results: For 13 four-month-olds tested thus far, performance in the BD condition was significantly above chance (50%) (p[[lt]]0.001) and the mean BDI was 0.48 (p=0.001). Conclusions: By four months of age, visual motion mechanisms are sensitive to depth-ordering (occlusion) cues. We are currently tracking the development of this phenomenon in infants of different ages.
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 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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.049 | 0.027 |
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".