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Record W2480383475 · doi:10.21037/jtd.2016.07.42

Mechanical ventilation in acute respiratory distress syndrome at ATS 2016: the search for a patient-specific strategy

2016· editorial· en· W2480383475 on OpenAlexaboutno aff
Mark Hepokoski, Robert L. Owens, Atul Malhotra, Jeremy R. Beitler

Bibliographic record

VenueJournal of Thoracic Disease · 2016
Typeeditorial
Languageen
FieldMedicine
TopicRespiratory Support and Mechanisms
Canadian institutionsnot available
FundersNational Heart, Lung, and Blood Institute
KeywordsARDSMedicineAcute respiratory distressIntensive care medicineDistressMechanical ventilationRespiratory distressVentilation (architecture)Mortality rateLungSurgeryPsychiatryInternal medicine

Abstract

fetched live from OpenAlex

Acute respiratory distress syndrome (ARDS) was first defined by Ashbaugh et al . in 1967 (1). They described 12 patients who developed the acute onset of hypoxemic respiratory failure, diffuse bilateral alveolar infiltrates, and low respiratory system compliance brought on by a variety of different insults. Decades of dedicated research have followed this initial description, yet ARDS remains a common critical illness with an exceptionally high mortality rate of 35–46% (2). At the 2016 American Thoracic Society (ATS) International Meeting, Dr. Brian Kavanagh, a Professor of Anesthesia from the University of Toronto, delivered a highly popular keynote speech addressing the role professional societies play in promoting universal management guidelines. He made several important points about the challenges and possible downsides to this strategy. This article reviews the potential for a more patient-specific approach to ARDS care based on presentations at the ATS meeting and the recent literature.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.051
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.030
GPT teacher head0.360
Teacher spread0.330 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEditorial

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

Citations5
Published2016
Admission routes1
Has abstractyes

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