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Tourette syndrome research highlights from 2022

2023· preprint· en· W4384201175 on OpenAlexaff
Andreas Hartmann, Per Andrén, Cyril Atkinson-Clément, Virginie Czernecki, Cécile Delorme, Nanette Mol Debes, Kirsten Müller‐Vahl, Peristera Paschou, Natalia Szejko, Apostolia Topaloudi, Keisuke Ueda, Kevin J. Black

Bibliographic record

VenueF1000Research · 2023
Typepreprint
Languageen
FieldPsychology
TopicObsessive-Compulsive Spectrum Disorders
Canadian institutionsUniversity of Calgary
FundersFP7 HealthFP7 People: Marie-Curie ActionsBiogenMinisterstwo ZdrowiaEuropean Stroke OrganisationNational Institute of Mental HealthDeutsche ForschungsgemeinschaftNational Science FoundationGW PharmaceuticalsNational Institute of Neurological Disorders and StrokeBundesministerium für Bildung und ForschungTourette Association of AmericaAmerican Brain FoundationNational Institutes of Health
KeywordsTourette syndromeNinthOpen peer reviewNeurosciencePlant biologyMedicinePsychologyPsychiatryBiology

Abstract

fetched live from OpenAlex

This is the ninth yearly article in the Tourette Syndrome Research Highlights series, summarizing selected research reports from 2022 relevant to Tourette syndrome. The authors briefly summarize reports they consider most important or interesting.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesResearch integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.804
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0050.009
Research integrity0.0020.010
Insufficient payload (model declined to judge)0.0430.078

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 head0.123
GPT teacher head0.438
Teacher spread0.315 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations6
Published2023
Admission routes1
Has abstractyes

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