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Record W7084053019 · doi:10.6084/m9.figshare.30026850

Additional file 1 of Sepsis in burn care: incidence and outcomes

2025· article· en· W7084053019 on OpenAlexaff

Bibliographic record

VenueOpen MIND · 2025
Typearticle
Languageen
FieldMedicine
TopicCancer Risks and Factors
Canadian institutionsMcMaster UniversityHamilton Health Sciences
Fundersnot available
KeywordsLogistic regressionSepsisUnivariate analysisIncidence (geometry)DemographicsUnivariate

Abstract

fetched live from OpenAlex

Additional file 1. Fig. S1 Study flow diagram showing patient inclusion and exclusion criteria. Fig. S2 Differences in survival outcomes among adult burn patients with sepsis, stratified by Gram stain classification of the pathogen identified at diagnosis. Fig. S3 Differences in survival outcomes among older adult burn patients with sepsis, stratified by Gram stain classification of the pathogen identified at diagnosis. Table S1 Demographics and injury characteristics of adult sepsis patients based on infectious pathogen classification. Table S2 Univariate logistic regression analyses in adult burn patients examining the association between various independent variables and sepsis diagnosis. Table S3 Univariate logistic regression analyses examining the association between various independent variables and mortality in adult burn patients diagnosed with sepsis. Table S4 Demographics and injury characteristics of older adult sepsis patients based on infectious pathogen classification. Table S5 Univariate logistic regression analyses examining the association between various independent variables and sepsis diagnosis in older adult burn patients. Table S6 Univariate logistic regression analyses examining the association between various independent variables and mortality in older adult burn patients diagnosed with sepsis

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.630
Threshold uncertainty score0.371

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)0.6300.000

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 head0.021
GPT teacher head0.340
Teacher spread0.319 · 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
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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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