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Record W3003640212 · doi:10.36425/2658-6843-19192

REATTACH FOR AUTISM: MAKING SENSE

2019· article· en· W3003640212 on OpenAlexaff
Paula Weerkamp-Bartholomeus

Bibliographic record

VenuePhysical and rehabilitation medicine medical rehabilitation · 2019
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsReach Technologies (Canada)
Fundersnot available
KeywordsAutismPsychologyIntervention (counseling)VitalityCognitionDevelopmental psychologyArousalCoherence (philosophical gambling strategy)PsychotherapistCognitive psychologyPsychiatryNeuroscience

Abstract

fetched live from OpenAlex

Autism Spectrum Disorders are a complex heterogenous group of clinical characteristics of which lack of central coherence and an atypical overall style of inter-personal reactions (forms of vitality) belong to the core symptomatology. Due to the number of individuals diagnosed with ASD that world-wide is growing rapidly, many research projects aim at detecting the underlying causes or mechanism or prevention and early intervention programs. ReAttach is an intervention for children and adults with ASD that facilitates arousal regulation, multiple sensory processing, coherence, social cognitive training and active learning. The method can be defined as a broader spectrum therapy, embracing neurodiversity and aiming at optimal health and personal and inter-relational development. The aim of this paper is to describe the ReAttach procedure and treatment outcome for ASD and to explain why ReAttach the involvement of parents and partners is required. The effects in terms of changes in clinical presentation and Forms of Vitality of individuals with ASD suggest that ReAttach is an accessible and cost-effective tool to overcome the developmental arrest in ASD.

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)0.003
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0020.004
Scholarly communication0.0030.006
Open science0.0010.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0080.004

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.

Opus teacher head0.018
GPT teacher head0.358
Teacher spread0.340 · 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 designQualitative
Domainnot available
GenreEmpirical

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
Published2019
Admission routes1
Has abstractyes

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