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Record W3107544999 · doi:10.1055/a-1287-2546

Gesundheitsökonomische Aspekte der Corona-Krise in der Schweiz: Resultate des COVID-19 Social Monitor

2020· article· de· W3107544999 on OpenAlexaff
Marc Höglinger, Beatrice Brunner, Michael Stucki, Simon Wieser

Bibliographic record

VenueGesundheitsökonomie & Qualitätsmanagement · 2020
Typearticle
Languagede
FieldEconomics, Econometrics and Finance
TopicCOVID-19 Pandemic Impacts
Canadian institutionsInstitute of Health Economics
Fundersnot available
KeywordsCoronavirus disease 2019 (COVID-19)Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)2019-20 coronavirus outbreakPolitical scienceGynecologyHumanitiesPhilosophyMedicineVirologyInternal medicine

Abstract

fetched live from OpenAlex

Zusammenfassung Nach Ausbruch der Corona-Pandemie wurde in der Schweiz Mitte März ein landesweiter Lockdown beschlossen. Dieser hatte extreme Auswirkungen auf das soziale Leben und die Gesundheitsversorgung. Der COVID-19 Social Monitor zeigt einige dieser gesellschaftlichen Veränderungen über die Zeit des Lockdowns und danach auf. Die Ergebnisse zeigen, dass in der akuten Phase des Lockdowns zwischen rund 50 % (Hausärzte) und über 90 % (Zahnärzte) der medizinischen Behandlungen nicht beansprucht wurden. Ausserdem brach die Arbeitsproduktivität massiv ein. Während des vollen Lockdowns lagen die Produktivitätsverluste bei durchschnittlich 46 %. Mit der schrittweisen Aufhebung des Lockdowns ab Ende April normalisierte sich die Lage weitgehend.

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)0.003
metaresearch head score (Gemma)0.006
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 score0.031
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
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 head0.180
GPT teacher head0.342
Teacher spread0.162 · 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

Citations3
Published2020
Admission routes1
Has abstractyes

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