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Record W1901328222 · doi:10.1007/bf03404951

Hospitalization for Ambulatory Care-Sensitive Conditions: A Method for Comparative Access and Quality Studies Using Routinely Collected Statistics

2001· article· en· W1901328222 on OpenAlexaffvenue
Adalsteinn Brown, Michael J Goldacre, Nicholas Hicks, James Rourke, Robert Y. McMurtry, John Brown, Geoffrey M. Anderson

Bibliographic record

VenueCanadian Journal of Public Health · 2001
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsUniversity of TorontoCanada Research ChairsSunnybrook Health Science CentreWestern University
Fundersnot available
KeywordsStatisticsAmbulatoryQuality (philosophy)MedicineMathematicsInternal medicine

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)0.177
metaresearch head score (Gemma)0.321
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: Methods · Consensus signal: Methods
Teacher disagreement score0.177
Threshold uncertainty score0.937

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1770.321
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0060.008
Bibliometrics0.0200.029
Science and technology studies0.0020.003
Scholarly communication0.0030.003
Open science0.0050.007
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0070.000

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 head0.532
GPT teacher head0.608
Teacher spread0.076 · 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
GenreMethods

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

Citations143
Published2001
Admission routes2
Has abstractno

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Same venueCanadian Journal of Public HealthSame topicPrimary Care and Health OutcomesFrench-language works237,207