The Screening Tool for Autism in Two Year Olds can identify children at risk of autism
Bibliographic record
Abstract
Stone WL, Coonrod EE, Turner LM, et al . Psychometric properties of the STAT for early autism screening. J Autism Dev Disord 2004;34:691–701.[OpenUrl][1][CrossRef][2][PubMed][3][Web of Science][4] Q How accurate is the Screening Tool for Autism in Two Year Olds (STAT) for identifying children at risk of autism? ### ![Graphic][5] Design: Diagnostic cohort study. ### ![Graphic][6] Setting: University based diagnostic evaluation centre and affiliated speech and hearing centre, Tennessee, USA; 1997 to 2001. ### ![Graphic][7] Patients: Initial validation of the STAT was carried out in 13 matched pairs of children aged 24–35 months, with a diagnosis of autism or alternatively developmental delay, language impairment, or both (DD/LI), and without severe sensory or motor impairment. Further validation was carried out in a sample of 104 children selected on the basis of parental report of developmental concerns. ### ![Graphic][8] Test: The STAT consists of 12 interactive items assessing different behavioural domains, including play, requesting, directing attention, and motor imitation. The test was administered by trained examiners who were blinded to the children’s diagnoses. Overall score ranges from 0 to 4, with lower … [1]: {openurl}?query=rft.jtitle%253DJournal%2Bof%2Bautism%2Band%2Bdevelopmental%2Bdisorders%26rft.stitle%253DJ%2BAutism%2BDev%2BDisord%26rft.aulast%253DStone%26rft.auinit1%253DW.%2BL.%26rft.volume%253D34%26rft.issue%253D6%26rft.spage%253D691%26rft.epage%253D701%26rft.atitle%253DPsychometric%2Bproperties%2Bof%2Bthe%2BSTAT%2Bfor%2Bearly%2Bautism%2Bscreening.%26rft_id%253Dinfo%253Adoi%252F10.1007%252Fs10803-004-5289-8%26rft_id%253Dinfo%253Apmid%252F15679188%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [2]: /lookup/external-ref?access_num=10.1007/s10803-004-5289-8&link_type=DOI [3]: /lookup/external-ref?access_num=15679188&link_type=MED&atom=%2Febmental%2F8%2F3%2F69.atom [4]: /lookup/external-ref?access_num=000225619900010&link_type=ISI [5]: /embed/inline-graphic-1.gif [6]: /embed/inline-graphic-2.gif [7]: /embed/inline-graphic-3.gif [8]: /embed/inline-graphic-4.gif
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.
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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 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".