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Record W2475626989 · doi:10.1192/bjp.193.6.517

Authors' reply

2008· article· en· W2475626989 on OpenAlexaff
Nick Craddock, Danny Antebi, Mary-Jane Attenburrow, Tony Bailey, Alan Carson, Philip J. Cowen, Klaus P. Ebmeier, Anne Farmer, Seena Fazel, Nicol Ferrier, John Geddes, Guy M. Goodwin, Paul Harrison, Keith Hawton, Stephen Hunter, Robin Jacoby, Ian Rees Jones, Paul Keedwell, Mike Kerr, Paul Mackin, Peter McGuffin, Donald McIntyre, Pauline McConville, Deborah Mountain, Michael O‘Donovan, Michael J. Owen, Femi Oyebode, Mary Phillips, Jonathan Price, Prem Shah, James Walters, Peter Woodruff, Allan H. Young, Stanley Zammit

Bibliographic record

VenueThe British Journal of Psychiatry · 2008
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicHealthcare Systems and Technology
Canadian institutionsUniversity of British Columbia
FundersCardiff UniversityUniversity of OxfordNewcastle UniversityUniversity of Pittsburgh
KeywordsContent (measure theory)Computer scienceAction (physics)MathematicsPhysics

Abstract

fetched live from OpenAlex

We are pleased that our article has stimulated debate. This was our intention. We are disappointed that some correspondents dismiss our argument by attacking a stereotype of who they think we are or a caricature of what they think we might have said, rather than addressing what we actually did say. Such correspondents have missed, or ignored, the point of the article – namely, to ask whether the de-medicalisation that has taken place over recent years in British psychiatry is bad for the health of patients and the specialty. We believe this is a question that is worth taking seriously. It is clear from the substantial correspondence and other feedback that many psychiatrists share our concerns and wish for constructive debate.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.073
Threshold uncertainty score0.500

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.018
GPT teacher head0.235
Teacher spread0.217 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations4
Published2008
Admission routes1
Has abstractyes

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