Bibliographic record
Abstract
Background: The peculiarities of sensory perception and perception of one's own body in children with autism are the basis for understanding their cognitive and social development difficulties. Objective: The study aims to structure different categories of drawings of children with autism and compare them with the severity of autism measured by CARS2. Methods: 120 children aged 3 to 9 years were studied (X= 6.26, SD = 3.16). Drawings of autistic children. The children have a white sheet, pencils, a children's drawing table, and the experimenter asks them to draw a person. The children were studied with CARS. 2. Clinical method: includes observation, direct work with the child on each of the topics of the methodology used, interview with parents, diagnostic discussion with the clinical team. Psychodiagnostic method: includes an examination of children with mental developmental stairs, assessment of cognitive, communication, socioemotional and sensorimotor functions. CARS 2 Childhood Autism Rating Scale | Second Edition Statistical. Method: includes data processing using the SPSS programme. Descriptive statistics, correlation analysis, a frequency distribution of data are used for data analysis. Results: The results show eight main categories of drawings in autistic children: 1. circles, water; 2. patches of colour covering the human figure or representing a human figure without an external boundary; 3. figures and letters; 4. human figures fenced as a bubble, a human figure composed of parts of objects (the elements are not connected); 5. objects with geometric shapes (buildings, roads with markings, apartment blocks, strange shells; 6. road signs, logos. Conclusions: There is no statistical dependence between the severity of autistic symptomatology and the types of drawings. We can draw some conclusions about how a child with autism perceives his own body from the presented results. Because we see that in mild and moderate degrees of autism CARS 2, the whole variety of drawing categories was evaluated, while in severe and very severe degrees of expression of the disorder circles, colourful spots with vague boundaries predominate. Children with autism often identify with non-living objects, street signs, eccentric houses and towers.
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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 | 0.000 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".