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Record W6939763224 · doi:10.6084/m9.figshare.17799332

Additional file 1 of Mechanical power in pediatric acute respiratory distress syndrome: a PARDIE study

2022· article· en· W6939763224 on OpenAlexaff

Bibliographic record

VenueOpen MIND · 2022
Typearticle
Languageen
FieldMedicine
TopicRespiratory Support and Mechanisms
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsMultivariable calculusTable (database)Mechanical ventilationAcute respiratory distressMechanical energyPower (physics)Operating tableMechanical ventilator

Abstract

fetched live from OpenAlex

Additional file 1. Table S1: Multivariable Analysis for Secondary Outcomes of 28-day VFD (IMV and NIV) and Time to Extubation in Survivors. Table S2: Propensity Score Multivariable Model for Use of High Mechanical Power (≥ 0.62 J min−1 Kg−1 predicted body weight). Table S3: Additional Sensitivity Analyses Limited to the Subgroup of Children <2 years of Age. Table S4: Multivariable models for the Association between Mechanical Energy and 28-day Ventilator-Free Days and Mortality. Table S5: The Univariable Association between each Ventilation Management Component of Mechanical Power and 28-day Ventilator-Free Days. Table S6: Multivariable Model for 28-day Ventilator-Free Days considering all Ventilator Management Components of Mechanical Power (with Delta Pressure) (n = 304). Table S7: Multivariable Model for 28-day Ventilator-Free Days considering all Ventilator Management Components of Mechanical Power (with Peak Inspiratory Pressure) (n=304). Table S8: Structural Equation Modeling. Figure S1: Distribution of Propensity Scores

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)0.002
metaresearch head score (Gemma)0.019
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: Dataset · Consensus signal: Dataset
Teacher disagreement score0.584
Threshold uncertainty score0.593

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.019
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.004
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.5840.052

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 head0.033
GPT teacher head0.308
Teacher spread0.275 · 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
GenreDataset

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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