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Record W3199699238 · doi:10.1007/s42650-021-00057-9

Population Health and COVID-19 in Canada: a Demographic Comparative Perspective

2021· editorial· en· W3199699238 on OpenAlexaffvenueabout
Daniela Ghio, Enrique Acosta, David N. Fisman, Andrew Noymer, Nikolaos I. Stilianakis, Simona Bignami

Bibliographic record

VenueCanadian Studies in Population · 2021
Typeeditorial
Languageen
FieldMathematics
TopicCOVID-19 epidemiological studies
Canadian institutionsUniversité de MontréalPublic Health OntarioUniversity of Toronto
Fundersnot available
KeywordsCoronavirus disease 2019 (COVID-19)Case fatality rateDemographyMortality ratePopulationExcess mortalitySevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)2019-20 coronavirus outbreakGeographyDiseaseMedicineOutbreakVirologySociologyInfectious disease (medical specialty)Pathology

Abstract

fetched live from OpenAlex

Demographers have been at the forefront of academic research about the burden of new coronavirus disease . Since the early work of This is because the age gradient of COVID-19 mortality is at least as steep as that of all-cause mortality, causing a greater concentration of deaths in old age Sex differentials in COVID-19 mortality are also more pronounced than all-cause mortality: COVID-19 mortality rates of men aged 25-80 have been found to be greater than those of women (Geldseltzer et al.,

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 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)0.042
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.744
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.042
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
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)0.0000.000

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 head0.310
GPT teacher head0.491
Teacher spread0.181 · 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 teacher head, not a consensus.

Study designNot applicable
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

Citations5
Published2021
Admission routes3
Has abstractyes

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