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Rapidly progressive diaphragmatic weakness and injury during mechanical ventilation in humans.

2011· preprint· en· W4298238523 on OpenAlexaff
Samir Jaber, Basil J. Petrof, Boris Jung, Gérald Chanques, Jean‐Philippe Berthet, Christophe Rabuel, Hassan Bouyabrine, Patricia Courouble, Christelle Koechlin‐Ramonatxo, Mustapha Sebbane, Thomas Similowski, Valérie Scheuermann, Alexandre Mebazaa, Xavier Capdevilla, Dominique Mornet, Jacques Mercier, Alain Lacampagne, Alexandre Philips, S. Matécki

Bibliographic record

VenueHAL (Le Centre pour la Communication Scientifique Directe) · 2011
Typepreprint
Languageen
FieldMedicine
TopicCongenital Diaphragmatic Hernia Studies
Canadian institutionsChristie (Canada)
Fundersnot available
KeywordsWeaknessMechanical ventilationDiaphragmatic breathingMedicinePhysical medicine and rehabilitationMuscle weaknessAnesthesiaInternal medicineSurgeryPathologyAlternative medicine

Abstract

fetched live from OpenAlex

International audience

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)0.001
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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.015
GPT teacher head0.249
Teacher spread0.234 · 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
Published2011
Admission routes1
Has abstractyes

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