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Record W4286702624 · doi:10.17147/asu-1-204756

COVID-19 als Berufskrankheit und Arbeitsunfall

2022· article· de· W4286702624 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueASU Arbeitsmedizin Sozialmedizin Umweltmedizin · 2022
Typearticle
Languagede
FieldHealth Professions
TopicMedical Practices and Rehabilitation
Canadian institutionsnot available
FundersCanadian Institutes of Health Research
KeywordsCoronavirus disease 2019 (COVID-19)GynecologyPhilosophyPhysicsMedicineInternal medicine

Abstract

fetched live from OpenAlex

COVID-19-Infektionen und somit auch deren möglichen Folgen können unter bestimmten Voraussetzungen als Berufskrankheit oder Arbeitsunfall anerkannt werden. Die Symptomatik und Ätiopathogenese von Post-COVID wird derzeit wissenschaftlich kontrovers diskutiert. Dennoch müssen bereits heute Personen mit Post-COVID für die Unfallversicherungsträger begutachtet werden. Daher wurde vom Autorenteam dieses Beitrags ein Vorschlag für eine Begutachtungsempfehlung erarbeitet, um eine standardisierte und damit vereinheitlichte Beurteilung unter Berücksichtigung des Unfallversicherungsrechts zu ermöglichen. Dieser wird hier zur Diskussion gestellt.

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.

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)0.026
metaresearch head score (Gemma)0.047
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.405
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0260.047
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0020.005
Science and technology studies0.0110.003
Scholarly communication0.0000.001
Open science0.0040.004
Research integrity0.0020.014
Insufficient payload (model declined to judge)0.1210.013

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 head0.094
GPT teacher head0.484
Teacher spread0.390 · 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