MétaCan
Menu
Back to cohort
Record W2410138357

[Origin of patients admitted involuntarily from an urban catchment area].

2008· article· en· W2410138357 on OpenAlexaboutno aff
Hans Chrisitan Schmidt, Hildegard Lindner, Theodor Zaunmüller

Bibliographic record

VenuePubMed · 2008
Typearticle
Languageen
FieldPsychology
TopicPsychiatric care and mental health services
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)Catchment areaCapital cityGeographyMedicineDemographySocioeconomicsDrainage basinArchaeologyCartographySociology
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVE: This investigation highlights some aspects of migration of patients between catchment areas. METHODS: From January till June 2003 all committed patients admitted from Linz, capital of the Austrian province Upper Austria, were investigated for their origin. RESULTS: Out of a total of 214 patients 111 (52%) were not native to Linz. Most stemmed from other counties of Upper Austria (55%), 16 (14%) were from other Austrian provinces and the remainder 32 (29%) were from foreign countries. In patients from other counties of Upper Austria 59% were already psychiatric ill before they had moved to Linz. Compared with patients native to Linz they displayed a greater number of psychiatric admissions, a greater number of cumulative hospital days and more often needed some measures of supported housing. More than a quarter of them had moved to Linz in the last 5 years. CONCLUSIONS: Results show that also in a well-established system of community psychiatric care a considerable number of patients is moving towards urban areas.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.001

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 head0.043
GPT teacher head0.294
Teacher spread0.251 · 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

Citations0
Published2008
Admission routes1
Has abstractyes

Explore more

Same venuePubMedSame topicPsychiatric care and mental health servicesFrench-language works237,207