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Record W3124195896 · doi:10.1002/ajim.23222

COVID‐19 as an occupational disease

2021· review· en· W3124195896 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAmerican Journal of Industrial Medicine · 2021
Typereview
Languageen
FieldMedicine
TopicInfection Control and Ventilation
Canadian institutionsUniversity of TorontoUniversity Health NetworkUniversity of British Columbia
FundersNational Center for Advancing Translational Sciences
KeywordsMedicinePandemicWorkforceDiseaseCoronavirus disease 2019 (COVID-19)Personal protective equipmentHealth careSocioeconomic statusIntensive care medicineEnvironmental healthInfectious disease (medical specialty)PathologyPopulationEconomic growth

Abstract

fetched live from OpenAlex

The impact of coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 permeates all aspects of society worldwide. Initial medical reports and media coverage have increased awareness of the risk imposed on healthcare workers in particular, during this pandemic. However, the health implications of COVID-19 for the global workforce are multifaceted and complex, warranting careful reflection and consideration to mitigate the adverse effects on workers worldwide. Accordingly, our review offers a framework for considering this topic, highlighting key issues, with the aim to prompt and inform action, including research, to minimize the occupational hazards imposed by this ongoing challenge. We address respiratory disease as a primary concern, while recognizing the multisystem spectrum of COVID-19-related disease and how clinical aspects are interwoven with broader socioeconomic forces.

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)0.001
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.990
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.151
GPT teacher head0.443
Teacher spread0.293 · 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