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Additional file 1 of The differential demographic pattern of coronavirus disease 2019 fatality outside Hubei and from six hospitals in Hubei, China: a descriptive analysis

2021· article· en· W6920818546 on OpenAlexaff

Bibliographic record

VenueOpen MIND · 2021
Typearticle
Languageen
FieldChemistry
TopicChemistry and Stereochemistry Studies
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsCase fatality rateIncidence (geometry)Mortality rateLife tableTable (database)EpidemiologyDiseaseCumulative incidence

Abstract

fetched live from OpenAlex

Additional file 1: Figure S1. Geographical distribution of case fatality rate of the COVID-19 patients based on the surveillance database in the mainland of China as of 29 March 2020. Table S1. The hospitalized case fatality rates of COVID-19 patients in related provinces. Table S2. The mortality rate and hospitalized case fatality rate of COVID-19 in China. Table S3. The hospitalized case fatality rate and relative risk for death outcome of COVID-19 patients by location, age, and sex. Table S4. The risk factor of fatal outcome among confirmed patients with SARS-COV-2 infection in the case-control study. Table S5. The cumulative incidence probability of death over time for the COVID-19 patients. Table S6. Clinical course of fatal cases and the factors associated with death among confirmed patients with SARS-COV-2 infection. Table S7. Comparison on the characteristics of fatal cases with SARS-COV-2 infection between severe and mild cases as of 29 March 2020.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.449
Threshold uncertainty score0.654

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.4490.000

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 head0.022
GPT teacher head0.262
Teacher spread0.241 · 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 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
Published2021
Admission routes1
Has abstractyes

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