Bibliographic record
Abstract
Recent attempts to measure spatial vision in infants have encountered serious drawbacks, such as the expense and sophistication of the equipment required, or the time necessary to complete the test. Adams, Mercer, Courage, and van Hof-van Duin (1992) have developed a prototype contrast sensitivity (CS) card procedure which sidesteps these problems, most notably test time. Despite its success, the prototype possesses several limitations which affect the accuracy and the efficiency of the procedure. -- In the present thesis, custom software and printing techniques were developed to construct a new set of CS cards which, compared to the prototype, contain four improvements: (1) Larger, more salient test gratings; (2) higher contrast "warm-up" cards in each spatial frequency set; (3) smaller contrast step size between adjacent cards; (4-) gratings mounted onto more durable backgrounds. The success of the new cards was evaluated by testing 3- and 12-month-old human infants and comparing the results to those obtained with the prototype cards. -- Results indicate that the new CS cards were very successful. Compared to the prototype, which required 10 to 15 minutes, the new card procedure was completed by most subjects within 5 to 8 minutes. Also, compared to the prototype, individual contrast sensitivity functions (CSFs) of 12-month-olds tested with the new cards are more typical of healthy infants as measured by more rigorous behavioral procedures. Surprisingly, however, group CSFs obtained with the new cards were lower than those obtained with the prototype, a discrepancy that may be due to differences in space average luminance between the two sets of cards. In all, the new CS card procedure possesses several merits which give it potential as a technique for widespread adoption by both researchers and clinicians. \n
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".