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Record W2024566803 · doi:10.1016/j.sleep.2013.02.016

Rapid eye movement sleep behavior disorder: devising controlled active treatment studies for symptomatic and neuroprotective therapy—a consensus statement from the International Rapid Eye Movement Sleep Behavior Disorder Study Group

2013· article· en· W2024566803 on OpenAlexaff
Carlos H. Schenck, J. Montplaisir, Birgit Frauscher, Birgit Högl, Jean Gagnon, Ronald B. Postuma, Karel Šonka, Poul Jennum, Markku Partinen, Isabelle Arnulf, Valérie Cochen De Cock, Yves Dauvilliers, Pierre‐Hervé Luppi, Anna Heidbreder, Geert Mayer, Friederike Sixel‐Döring, Claudia Trenkwalder, Marcus M. Unger, Peter Young, Yun Kwok Wing, Luigi Ferini‐Strambi, Raffaele Ferri, Giuseppe Plazzi, Marco Zucconi, Yuichi Inoue, A. Iranzo, Joan Santamaría, Claudio L. Bassetti, Jens Carsten Möller, Bradley F. Boeve, Y.-Y. Lai, Milena Pavlova, Clifford B. Saper, Péter Schmidt, Judith M. Siegel, Carlos Singer, Erik K. St. Louis, Aleksandar Videnović, Wolfgang H. Oertel

Bibliographic record

VenueSleep Medicine · 2013
Typearticle
Languageen
FieldMedicine
TopicRestless Legs Syndrome Research
Canadian institutionsMcGill UniversityMontreal General HospitalUniversité de MontréalHôpital du Sacré-Cœur de Montréal
FundersNational Institute of Neurological Disorders and StrokeNational Institute on Drug AbuseU.S. Department of Veterans Affairs
KeywordsREM sleep behavior disorderDementia with Lewy bodiesRapid eye movement sleepMedicineMovement disordersNeuroprotectionRandomized controlled trialCognitive declineParasomniaDementiaPsychiatryPsychologyPediatricsParkinson's diseaseDiseaseSleep disorderCognitionInternal medicineElectroencephalography

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.265
metaresearch head score (Gemma)0.198
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.265
Threshold uncertainty score0.906

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2650.198
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0150.009
Bibliometrics0.0030.003
Science and technology studies0.0040.005
Scholarly communication0.0090.006
Open science0.0090.004
Research integrity0.0190.017
Insufficient payload (model declined to judge)0.0020.001

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 head0.047
GPT teacher head0.359
Teacher spread0.312 · 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.

Study designNot applicable
Domainnot available
GenreCommentary

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

Citations233
Published2013
Admission routes1
Has abstractno

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