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Record W3021554968 · doi:10.51893/2020.2.ed2

Opportunities and challenges of clustering, crossing over, and using registry data in the PEPTIC trial

2020· article· en· W3021554968 on OpenAlexaff
Paul J. Young, Sean M. Bagshaw, Andrew Forbes, Alistair Nichol, Stephen E. Wright, Rinaldo Bellomo, Frank van Haren, Edward Litton, Steve Webb

Bibliographic record

VenueCritical Care and Resuscitation · 2020
Typearticle
Languageen
FieldMedicine
TopicAntibiotics Pharmacokinetics and Efficacy
Canadian institutionsUniversity of Alberta Hospital
Fundersnot available
KeywordsMedicineCluster analysisPepticData miningPeptic ulcerInternal medicineArtificial intelligenceComputer science

Abstract

fetched live from OpenAlex

The Proton Pump Inhibitors (PPIs) versus Histamine-2 Receptor Blockers (H2RBs) for Ulcer Prophylaxis Therapy in the Intensive Care Unit (ICU) (PEPTIC) trial is the largest randomised clinical trial ever conducted in the field of intensive care medicine. The potential clinical implications of the trial have been the subject of a previous editorial. Here we focus on the implications of the study for clinical trial science and on the opportunities the study provides for exploratory analyses that will potentially shed further light on the relative safety and efficacy of using PPIs or H2RBs for stress ulcer prophylaxis in the critically ill.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.395
Threshold uncertainty score0.157

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.321
GPT teacher head0.420
Teacher spread0.099 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations3
Published2020
Admission routes1
Has abstractyes

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