Editorial Perspective: Longitudinal research in autism – introducing the concept of ‘chronogeneity’
Bibliographic record
Abstract
Autism Spectrum Disorder (ASD or autism) is a heterogeneous neurodevelopmental disorder. We are now at a critical juncture in autism research where we have the knowledge base and expertise to begin to think about studies that view heterogeneity, not as 'statistical noise' that can be 'accounted for' using data-reduction techniques (such as group trajectories), but rather as 'informative variance' that can help form a more precise and dynamic picture of autism. In this Editorial we coin a new term and introduce the concept of 'chronogeneity' for the study of autism heterogeneity in relation to the dimension of time (chrono). Using examples of ongoing research and analytical advances we build the case for the potential utility of the concept of 'chronogeneity' and argue that a refined approach to the longitudinal investigation of autism (and other neurodevelopmental disorders) may move us closer to more precise and adaptive models of care for the children and youth affected by these disorders.
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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 | 0.011 | 0.043 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.020 | 0.028 |
| Insufficient payload (model declined to judge) | 0.008 | 0.007 |
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".