MétaCan
Menu
Back to cohort
Record W3042529820 · doi:10.7861/clinmed.let.20.4.8

Is computed tomography really the future of biology for diagnosing COVID-19 infection?

2020· letter· en· W3042529820 on OpenAlexaff
Jean-François Vendrell, Jean-Pierre Vendrell, G. Gahide

Bibliographic record

VenueClinical Medicine · 2020
Typeletter
Languageen
FieldMedicine
TopicCOVID-19 diagnosis using AI
Canadian institutionsCentre Hospitalier Universitaire de Sherbrooke
Fundersnot available
KeywordsCoronavirus disease 2019 (COVID-19)MedicineOutbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)2019-20 coronavirus outbreakComputed tomographyInfection controlDisease controlCoronavirus InfectionsVirologyMedical emergencyIntensive care medicineMedical physicsDiseasePathologyInfectious disease (medical specialty)Radiology

Abstract

fetched live from OpenAlex

Editor – Though the COVID-19 outbreak has now reached every continent and contaminated more than 1 million people causing tens of thousands of deaths and the lockdown of almost 3 billion people. To confirm the diagnosis, the Centers for Disease Control and Prevention recommends the collection of

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)0.002
metaresearch head score (Gemma)0.015
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.045
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.015
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0020.004
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 head0.108
GPT teacher head0.452
Teacher spread0.344 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreCommentary

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
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueClinical MedicineSame topicCOVID-19 diagnosis using AIFrench-language works237,207