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Record W1936262166 · doi:10.1007/s00134-015-3854-6

Impact of sedation and analgesia during noninvasive positive pressure ventilation on outcome: a marginal structural model causal analysis

2015· article· en· W1936262166 on OpenAlexaff
Alfonso Muriel, Óscar Peñuelas, Fernando Frutos–Vivar, Alejandro C. Arroliga, Víctor Abraira, Arnaud W. Thille, Laurent Brochard, Nicolás Nín, Andrew R. Davies, Pravin Amin, Bin Du, Konstantinos Raymondos, Fernando Ríos, Damian A. Violi, Salvatore Maurizio Maggiore, Márcio Soares, Marco González, Fekri Abroug, Hans-Henrik Bülow, Javier Hurtado, Michaël Kuiper, Rui P. Moreno, Amine Ali Zeggwagh, Asisclo Villagómez, Manuel Jibaja, Luis Soto, Gabriel D’Empaire, Dimitrios Matamis, Younsuck Koh, Antonio Anzueto, Niall D. Ferguson

Bibliographic record

VenueIntensive Care Medicine · 2015
Typearticle
Languageen
FieldMedicine
TopicNosocomial Infections in ICU
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
FundersInstituto de Salud Carlos III
KeywordsMedicineSedativeOdds ratioSedationAnesthesiaAnalgesicConfidence intervalMechanical ventilationAnesthesiologyIntensive careIntensive care medicineInternal medicine

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.029
metaresearch head score (Gemma)0.084
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.038
Threshold uncertainty score0.154

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0290.084
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0050.009
Bibliometrics0.0020.001
Science and technology studies0.0020.003
Scholarly communication0.0030.003
Open science0.0050.004
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0150.001

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 head0.036
GPT teacher head0.367
Teacher spread0.332 · 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.

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

Citations60
Published2015
Admission routes1
Has abstractno

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