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Additional file 5 of Association of immediate reinsertion of new catheters with subsequent mortality among patients with suspected catheter infection: a cohort study

2022· article· en· W6958291517 on OpenAlexaff

Bibliographic record

VenueFigshare · 2022
Typearticle
Languageen
FieldHealth Professions
TopicCentral Venous Catheters and Hemodialysis
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsPropensity score matchingSepsisCentral venous catheterCatheterCohortRetrospective cohort studyCohort study

Abstract

fetched live from OpenAlex

Additional file 5: Table S1. Diagnostic criteria for suspected sepsis in adults according to the 2001 International Sepsis Definitions Conference. Table S2. Total sample size and crude number of admissions experiencing the outcome for competing risk analysis. Table S3. Baseline characteristics of patients who underwent central venous catheter removal for suspected infection, according to IRINC or not, before and after propensity score matching. Table S4. Causative pathogens of CRBSI after suspected infection in all patients. Table S5. Comparison of causative pathogens between patients who underwent IRINC and those who did not undergo IRINC among patients with CRBSI after propensity score matching. Table S6. Baseline characteristics of patients who underwent central venous catheter removal for suspected infection, according to IRINC or not, before and after propensity score matching and inverse probability of treatment weighting in the subgroup with catheter-related bloodstream infections. Table S7. Baseline characteristics of patients who underwent central venous catheter removal for suspected infection, according to IRINC or not, before and after propensity score matching in the subgroup without catheter-related bloodstream infection.

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)0.001
metaresearch head score (Gemma)0.031
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: Observational · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.711
Threshold uncertainty score0.412

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.031
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.004
Science and technology studies0.0010.000
Scholarly communication0.0010.002
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.7110.039

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 head0.024
GPT teacher head0.280
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 source (direct Gemma or distilled Codex), not a consensus.

Study designObservational
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
Published2022
Admission routes1
Has abstractyes

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