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Additional file 2 of Prophylactic antibiotics for preventing ventilator-associated pneumonia: a pairwise and Bayesian network meta-analysis

2023· article· en· W6939651501 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2023
Typearticle
Languageen
FieldMedicine
TopicNosocomial Infections in ICU
Canadian institutionsnot available
Fundersnot available
KeywordsObservational studyForest plotIncidence (geometry)Duration (music)Meta-analysisPairwise comparisonFunnel plotBayesian network

Abstract

fetched live from OpenAlex

Additional file 2: Table S1. The quality assessments of observational studies using Newcastle-Ottawa Scale score. Figure S1. The quality assessments of interventional studies using risk of bias tool 2 (ROB2)recommended by the Cochrane Collaboration. Figure S2. Forest plots of the effect of prophylactic antibiotics compared with placebo, on the duration of invasive ventilation. Studies are grouped by the routes of administration. Figure S3. Forest plots of the effect of prophylactic antibiotics, compared with placebo, on the duration of ICU stay. Studies are grouped by the route of administration. Figure S4. Forest plots of the effect of prophylactic antibiotics compared with placebo, on the duration of hospitalization. Studies are grouped by the route of administration. Figure S5. Forest plots of the effect of prophylactic antibiotics, compared with placebo, on adverse events. Studies are grouped by the route of administration. Figure S6. Funnel plot of the included studies for incidence of VAP. Figure S7. Sensitivity analyses on the incidence of VAP. Figure S8. GRADE assessment of a) randomized controlled studies and b) observational studies.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.099
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.830
Threshold uncertainty score0.243

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.099
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.006
Bibliometrics0.0060.007
Science and technology studies0.0010.000
Scholarly communication0.0030.003
Open science0.0030.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.8300.041

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 head0.088
GPT teacher head0.312
Teacher spread0.224 · 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 source (direct Gemma or distilled Codex), not a consensus.

Study designMeta-analysis
Domainnot available
GenreOther

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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