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Record W4386618288 · doi:10.1055/a-2080-8566

Die Mortalität von Menschen mit Schizophrenie bei Hitze

2023· article· de· W4386618288 on OpenAlexaboutno aff

Bibliographic record

VenuePsychiatrische Praxis · 2023
Typearticle
Languagede
FieldEnvironmental Science
TopicClimate Change and Health Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceHumanitiesPhilosophyGynecologyMedicine

Abstract

fetched live from OpenAlex

Fast wäre die Studie “Chronic Diseases Associated With Mortality in British Columbia, Canada During the 2021 Western North America Extreme Heat Event” in der Zeitschrift GeoHealth 1 an der psychiatrischen Fachwelt vorbeigegangen. GeoHealth ist eine Open-Access- Zeitschrift (Impact Faktor 6,3), die sich selbst als transdisziplinär bezeichnet und an den „intersections of the Earth and environmental sciences and health sciences“ interessiert ist und gehört wahrscheinlich nicht zu den Zeitschriften, die von in der Psychiatrie Tätigen routinemäßig gelesen werden. Auch der Autor dieses Beitrages wurde erst durch einen Artikel eines Wissenschaftsjournalisten in Science (Schizophrenia pinpointed as a key factor in heat deaths; 2) darauf aufmerksam. Doch dieser Artikel hat es in sich. Die Studie einer Gruppe von Epidemiologen aus British Columbia um Lee et al. in GeoHealth zeigt erstmals in dieser Deutlichkeit, wie hoch die Mortalität gerade von Menschen mit psychiatrischen Erkrankungen, insbesondere aber von Menschen mit Schizophrenie, an Hitzetagen ist.

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)0.002
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 score0.617
Threshold uncertainty score0.771

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0020.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.048
GPT teacher head0.323
Teacher spread0.274 · 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
Published2023
Admission routes1
Has abstractyes

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