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Record W4296326252 · doi:10.1111/jsr.13722

Focus on sleep medicine

2022· editorial· en· W4296326252 on OpenAlexaboutno aff
Dieter Riemann

Bibliographic record

VenueJournal of Sleep Research · 2022
Typeeditorial
Languageen
FieldPsychology
TopicSleep and related disorders
Canadian institutionsnot available
Fundersnot available
KeywordsDementiaSleep medicineNeurocognitiveSleep apneaMedicinePsychologyPsychiatryDiseaseGerontologySleep disorderCognitionInternal medicine

Abstract

fetched live from OpenAlex

Dear readers of the Journal of Sleep Research (JSR), Let me welcome you to the fifth issue of the JSR in 2022.In the meantime, the ESRS conference in Athens has passed and I would like to thank all those who attended in person and celebrated the 50th anniversary of the ESRS.Many of you will have received the special print issue to celebrate the 50th anniversary and I hope you still enjoy browsing through the contents.This fifth issue of JSR in 2022 encompasses a broad variety of articles coming from the fields of sleep research and sleep medicine, although this time there is a majority of articles dealing with sleep medicine topics.

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)0.004
metaresearch head score (Gemma)0.014
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: Not applicable
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.061
Threshold uncertainty score0.203

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.014
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0030.002
Science and technology studies0.0020.003
Scholarly communication0.0070.008
Open science0.0020.005
Research integrity0.0070.011
Insufficient payload (model declined to judge)0.0610.029

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 head0.052
GPT teacher head0.426
Teacher spread0.375 · 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
GenreEditorial

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
Published2022
Admission routes1
Has abstractyes

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