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Record W2189094050

How to approach pediatric sleep medicine in British Columbia: A consensus paper

2008· article· en· W2189094050 on OpenAlexaboutno aff
O. Ipsiroglu, James E. Jan, Roger D. Fréeman, Alison J. Laswick, Ruth Milner, Craig Mitton, Michael Wasdell, David Wensley, William H. McKellin

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPsychology
TopicSleep and related disorders
Canadian institutionsnot available
Fundersnot available
KeywordsSleep (system call)Sleep medicinePublic healthHealth careMEDLINEFamily medicineMedicinePsychologySleep disorderNursingPsychiatryPolitical scienceComputer science
DOInot available

Abstract

fetched live from OpenAlex

Children's sleep prob- lems are currently not a high priori- ty at BC Children's Hospital (BCCH) or at other children's hospitals throughout Canada, nor has sleep been identified as a public health issue, which has to be addressed in a structured way. However, the inter- national literature clearly shows the importance of prevention activities related to pediatric sleep problems, as well as the need to implement sleep services at different levels in the health care system. In order to determine the pediatric sleep medi- cine needs in BC, the Sleep Research Group at BCCH organized a consen- sus meeting in June 2007. Partici- pants included members of the clin- ical research team at BCCH, invited health care professionals, and guest speakers with expertise in pediatric sleep medicine, sleep measure- ment, and health economics. During the 1-day workshop, participants discussed how the existing gaps in pediatric sleep medicine in BC could be closed and how care for pediatric sleep problems could be delivered at the provincial level. This proposal, based on the published consensus, will form the basis to advocate for improved services in BC.

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)0.036
metaresearch head score (Gemma)0.038
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: Other · Consensus signal: none
Teacher disagreement score0.520
Threshold uncertainty score0.955

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0360.038
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.006
Science and technology studies0.0060.003
Scholarly communication0.0060.004
Open science0.0060.005
Research integrity0.0090.011
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 head0.016
GPT teacher head0.240
Teacher spread0.224 · 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
GenreOther

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

Citations3
Published2008
Admission routes1
Has abstractyes

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