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Record W4236927477 · doi:10.1192/02-620

Distribution and characteristics of in-patient child and adolescent mental health services in England and Wales

2003· article· en· W4236927477 on OpenAlexfundno aff
Anne O’Herlihy, Adrian Worrall, Paul Lelliott, Tony Jaffa, Peter Hill, Sube Banerjee

Bibliographic record

VenueThe British Journal of Psychiatry · 2003
Typearticle
Languageen
FieldHealth Professions
TopicChild and Adolescent Health
Canadian institutionsnot available
FundersHospital for Sick Children
KeywordsMental healthProject commissioningDistribution (mathematics)Service (business)MedicineTelephone surveyPsychiatryHealth servicesMental health serviceFamily medicinePublishingEnvironmental healthBusinessPolitical scienceAdvertisingMarketing

Abstract

fetched live from OpenAlex

Background Little is known about the current state of provision of child and adolescent mental health service in-patient units in the UK. Aims To describe the full number, distribution and key characteristics of child and adolescent psychiatric in-patient units in England and Wales. Method Following identification of units, data were collected by a postal general survey with telephone follow-up. Results Eighty units were identified; these provided 900 beds, of which 244 (27%) were managed by the independent sector. Units are unevenly distributed, with a concentration of beds in London and the south-east of England. The independent sector, which manages a high proportion of specialist services and eating disorder units in particular, accentuates this uneven distribution. Nearly two-thirds of units reported that they would not accept emergency admissions. Conclusions A national approach is needed to the planning and commissioning of this specialist service.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.034
Threshold uncertainty score0.067

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.009
GPT teacher head0.295
Teacher spread0.286 · 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 designObservational
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

Citations13
Published2003
Admission routes1
Has abstractyes

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