Bibliographic record
Abstract
Asperger's Syndrome, edited by Ami Klin and colleagues of the Yale University Child Study Center, contains contributions from 27 authors representing 13 universities, and several agencies and clinical practices in the United Kingdom, Canada, and the USA. This is a thorough and sorely needed review of the research, diagnostic process, treatment options, and outcomes associated with Asperger's syndrome (AS). Written for professionals, the volume is research-based, and in this relatively new field of study, is as useful in elucidating the questions still requiring investigation as in describing what is currently known. Several aspects of diagnosis are covered, including the development of AS as a formal diagnostic category, a review of clinical features and associated conditions, differential diagnostic considerations (particularly high functioning Autism, Schizoid Personality Disorder, developmental language disorders, and Nonverbal Learning Disability), and special consideration of the contributions of motor functioning, social language use, and neuropsychological functioning to differential diagnosis. Of special interest to neuropsychologists may be the chapter reviewing neuropsychological and neuroimaging studies of AS, from which inferences can be drawn about potential neurodevelopmental processes leading to the manifestations of this disorder. Other chapters focus on genetic factors, clinical outcomes in adolescence and adulthood, pharmacological intervention, and general treatment considerations. A chapter on assessment suggests practical guidelines for assessment of cognitive, neuropsychological, communicative, social–emotional, and adaptive functioning. A set of essays by parents closes the volume, providing an important reconnection to the everyday challenges faced by individuals with AS and their families.
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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.007 |
| Insufficient payload (model declined to judge) | 0.010 | 0.004 |
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".