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Record W2804008011

Diagnosis “Autism†– from Kanner and Asperger to DSM-5

2014· article· en· W2804008011 on OpenAlexvenueno aff
Meglena Achkova, Harieta Manolova

Bibliographic record

VenueJournal of Intellectual Disability - Diagnosis and Treatment · 2014
Typearticle
Languageen
FieldPsychology
TopicPsychology of Development and Education
Canadian institutionsnot available
Fundersnot available
KeywordsAutismContext (archaeology)Identification (biology)PsychologyPopulationData scienceDevelopmental psychologyMedicineComputer science
DOInot available

Abstract

fetched live from OpenAlex

The authors make a synthesized overview of the evolution of the understanding of autism in historical context and a critical analysis of the development of diagnostic criteria in the spirit of the Diagnostic and Statistical Manual (DSM). Based on personal research and extensive clinical experience they put forward a number of debatable issues and own views about the nature of autistic disorder by outlining the trends and directions for future research. Discussed is the issue of core and additional symptoms of autism and the need for comparison of categorical and dimensional data when constructing empirical studies for the autistic population. The article contains reflections on the underlying impairment which, according to the authors, is a disturbance in the processing and integration of the incoming information, especially at the level of filtration of significant and insignificant stimuli and their linking into a mental sequence appearing at different levels and with varying degree of severity. Noted is the importance of the detailed assessment of mental functioning for early diagnosis and individualized targeting of the therapeutic efforts. In this regard is emphasized the need to search for a new paradigm in the methodology of future research on autism that would make possible the comparison of interdisciplinary results and identification of connections between the relevant scientific achievements. Thus it will be possible to identify trends that will bring us closer to revealing the etiology, perhaps will have an impact on the criteria for diagnosis and on the overall construction of future therapeutic strategies.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0020.002
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.044
GPT teacher head0.330
Teacher spread0.286 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations0
Published2014
Admission routes1
Has abstractyes

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Same venueJournal of Intellectual Disability - Diagnosis and TreatmentSame topicPsychology of Development and EducationFrench-language works237,207