Oculographic indicators while performing the ‘pick the odd item’ task: A study of children with disabilities aged 6–7 years
Bibliographic record
Abstract
The article presents the results of a study of visual perception in children 6–7 years old when picking the odd item according to the Fourth Odd method by L. M. Shipitsina with parallel registration of oculographic indicators using the Gazepoint GP3 HD eye tracker (150 Hz, Canada). The sample included 86 pupils of preschool educational institutions of Saint Petersburg aged of 6–7 years (mean age 6.5 years): 51 normal children (group 1), 20 children with a hard speech disorder (group 2), and 15 children with mental retardation (group 3). The stimuli were five pictures, each with four objects, from the Fourth Odd method by L. M. Shipitsina. The pictures were displayed on a computer screen and sequentially presented to the child. The study found statistically significant differences in the number of fixations on the background: there were a greater number of fixations in children with mental retardation than in normal children. There are also significant differences in the duration of fixations on objects: normal children have longer fixations than children with mental retardation. The results will be useful for specialists who work with children with disabilities.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".