MétaCan
Menu
Back to cohort
Record W3016366678 · doi:10.5770/cgj.23.445

COVID-19 and Older Adults. Lessons Learned from the Italian Epicenter

2020· article· en· W3016366678 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.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueCanadian Geriatrics Journal · 2020
Typearticle
Languageen
FieldMedicine
TopicFrailty in Older Adults
Canadian institutionsParkwood InstituteLawson Health Research InstituteWestern University
Fundersnot available
KeywordsMedicinePandemicCoronavirus disease 2019 (COVID-19)Mortality ratePresentation (obstetrics)PediatricsHealth careDiseaseInfectious disease (medical specialty)Surgery

Abstract

fetched live from OpenAlex

On March 13th, 2020, The World Health Organization effectively established that Europe is the new the COVID-19 pandemic world epicenter, as cases in Italy and other European nations soared. The numbers in Italy have climbed with over 80,000 cases as of March 25th, 2020 and with over 8000 deaths, placing Italy now as the country with the highest mortality rate. Importantly, older adults are particularly vulnerable to get severe illness, complications, and to have a higher mortality rate than any other age group. The clinical presentation in older adults with severe illness, in the experience from geriatricians in Lombardy, is described as quite sudden; patients can develop severe hypoxemia with the need of ventilation support in few hours. Geriatric syndromes are not a common form of presentation for COVID-19 in severe illness. It is suggested that stratification by frailty level may help to detect the most vulnerable, and decisions about healthcare resource prioritization should not be taken based only on age itself or previous diagnosis, such as having dementia.

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)0.000
metaresearch head score (Gemma)0.002
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.758
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
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 science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.053
GPT teacher head0.294
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