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Record W3061000689 · doi:10.1016/s2214-109x(20)30365-x

Clinical trials of disease stages in COVID 19: complicated and often misinterpreted

2020· article· en· W3061000689 on OpenAlexaff
Jay Park, Eric Decloedt, Craig R. Rayner, Mark F. Cotton, Edward J. Mills

Bibliographic record

VenueThe Lancet Global Health · 2020
Typearticle
Languageen
FieldMedicine
TopicCOVID-19 Clinical Research Studies
Canadian institutionsMcMaster UniversityImpactUniversity of British Columbia
Fundersnot available
KeywordsClinical trialMedicineCoronavirus disease 2019 (COVID-19)Protocol (science)MEDLINEFamily medicinePsychological interventionDiseaseIntensive care medicineAlternative medicineInternal medicinePathologyInfectious disease (medical specialty)Nursing

Abstract

fetched live from OpenAlex

As of July 28, 2020, 1840 clinical trials were registered globally, with 1001 clinical trials recruiting patients for COVID-19 management.1 Despite this large number, only 30 trials have been published as peer-reviewed or preprint publications.2 Media reports and prepublications on medRxiv and bioRxiv represent the most frequent mechanism for data sharing, with wide public reach and usually with little detail. However, with inadequate details on the trials and only superficial scrutiny by the public and scientific decision makers, the consequences have had disastrous effects on other clinical trial funding, permissions, recruitment, and interpretation.

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)0.008
metaresearch head score (Gemma)0.135
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.703
Threshold uncertainty score0.873

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.135
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.363
GPT teacher head0.618
Teacher spread0.255 · 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

Citations32
Published2020
Admission routes1
Has abstractyes

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