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Record W3016733568 · doi:10.1055/s-0040-1710145

Better Safe than Sorry: Interventional Radiology Should Be Prepared for the Coronavirus Disease 2019 Pandemic

2020· article· en· W3016733568 on OpenAlexaboutno aff
Arul Babu, Aswin Padmanabhan, Pushpinder Singh Khera, Hemant Sonwalkar

Bibliographic record

VenueJournal of Clinical Interventional Radiology ISVIR · 2020
Typearticle
Languageen
FieldMedicine
TopicCOVID-19 and healthcare impacts
Canadian institutionsnot available
Fundersnot available
KeywordsPandemicCoronavirus disease 2019 (COVID-19)Transmission (telecommunications)Quarter (Canadian coin)CoronavirusDiseaseSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)MedicinePneumonia2019-20 coronavirus outbreakIntensive care medicineMedical emergencyFamily medicineVirologyInfectious disease (medical specialty)HistoryComputer sciencePathologyInternal medicineTelecommunications

Abstract

fetched live from OpenAlex

Abstract Coronavirus disease 2019 (COVID-19) is a viral pneumonia that has plagued the world for much of the first quarter of 2020 and was recently declared a global pandemic. The caregivers must be aware of the disease and take steps to curb its transmission within the premises of our care settings (hospitals/clinics). In this article, we suggest a few proactive steps that can be taken at the institutional and departmental levels to break the transmission chain.

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)0.004
metaresearch head score (Gemma)0.010
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.324
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.446
GPT teacher head0.558
Teacher spread0.112 · 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

Citations6
Published2020
Admission routes1
Has abstractyes

Explore more

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