Behavioral pattern profile: A tool for the description of behavior to be used in the genetics clinic
Bibliographic record
Abstract
Careful descriptions of dysmorphic features have led to the delineation of hundreds of specific syndromes and patterns of congenital anomalies. The defining of unusual behavior had largely been neglected by clinical geneticists until the study of the natural history of microdeletions revealed that each has unique and characteristic behavior(s). In this study, a simple tool to describe behavior is presented that is to be used in the genetics clinic as part of routine evaluation. The form is meant to simplify recording and does not require the formal training needed for psychological assessments. It is hoped that routine recording of behavior among individuals seen in the genetics clinic will lead to better recognition of unusual behavior among individuals with known conditions, as well as the recognition of conditions characterized only by unusual behavior. Better description of behavioral patterns should lead to the ascertainment of homogeneous groups of affected individuals with abnormalities in the functional pathways that generate patterns of reaction. The genetic and biochemical basis for these patterns of reaction (abnormal behavior) should then be available for both natural history and molecular studies. The tool consists of 12 categories of behavioral features that can be assessed by the medical geneticist. The list was built to allow the observation of as many behavioral aspects as possible, but to keep it to a practical size and to use those features that are simple to describe and quantitate. We expect that its use will produce a rich source of behavioral profiles and will eventually contribute to the better understanding of unusual behavior.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.034 | 0.016 |
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".