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Record W6962858635 · doi:10.17632/d58x978jrh.1

Small-molecule antivirals treatment for Covid-19: A systematic review and network meta-analysis

2023· dataset· en· W6962858635 on OpenAlexaboutno aff

Bibliographic record

VenueData Archiving and Networked Services (DANS) · 2023
Typedataset
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPharmacological Receptor Mechanisms and Effects
Canadian institutionsnot available
Fundersnot available
KeywordsSystematic reviewBlindingProtocol (science)Retrospective cohort studyMEDLINERandomized controlled trialComparability

Abstract

fetched live from OpenAlex

Supplemental Materials for "Small-molecule antivirals treatment for Covid-19: A systematic review and network meta-analysis". Our study was registered on PROSPERO (CRD42023396617) and followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines. The protocol was also showed . The study characteristics about 92 RCTs and 68 retrospective studies were shown. We utilized the revised Cochrane Risk of Bias tool for RCTs and the Newcastle Ottawa Scale (NOS) for retrospective studies. A total of 92 RCTs were included, of which 42 RCTs were comprehensively evaluated as "High risk" due to allocation concealment and blinding, 15 RCTs were evaluated as "Unclear risk" due to blinding and other biases. A total of 67 retrospective studies were included, of which 34 were mainly downgraded for the typicality of the exposed study, comparability of studies on the basis of the design or analysis, and adequacy of follow up of cohorts.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.593
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
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 head0.118
GPT teacher head0.363
Teacher spread0.245 · 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
GenreDataset

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
Published2023
Admission routes1
Has abstractyes

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