Early Autism Detection: Are We Ready for Routine Screening?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
UNLABELLED: BACKGROUND. Autism is a serious neurodevelopmental disorder that has a reportedly rising prevalence rate. The American Academy of Pediatrics recommends that screening for autism be incorporated into routine practice. It is important to consider the pros and cons of conducting autism screening as part of routine practice and its implications on the community. We have explored this question in the context of screening from a scientific point of view. METHOD: A literature search was conducted to assess the effectiveness of community screening programs for autism. RESULTS: Judged against critical questions about autism, screening programs failed to fulfill most criteria. Good screening tools and efficacious treatment are lacking, and there is no evidence yet that such a program would do more good than harm. CONCLUSIONS: On the basis of the available research, we believe that we do not have enough sound evidence to support the implementation of a routine population-based screening program for autism. Ongoing research in this field is certainly needed, including the development of excellent screening instruments and demonstrating with clinical trials that such programs work and do more good than harm.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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 it