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Record W2026842455 · doi:10.1517/14728214.2012.667800

Emerging therapies for treatment of acute lung injury and acute respiratory distress syndrome

2012· letter· en· W2026842455 on OpenAlexaff
Cory Yamashita, James F. Lewis

Bibliographic record

VenueExpert Opinion on Emerging Drugs · 2012
Typeletter
Languageen
FieldMedicine
TopicRespiratory Support and Mechanisms
Canadian institutionsSt Joseph's Health CentreLondon Health Sciences CentreWestern University
Fundersnot available
KeywordsMedicineARDSIntensive care medicineAcute respiratory distressDiseaseClinical trialPsychological interventionLungInternal medicinePsychiatry

Abstract

fetched live from OpenAlex

In 2007, Bosma et. al provided a comprehensive review of emerging therapies for the acute respiratory distress syndrome (ARDS), a condition which continues to carry a mortality rate of greater than 30%. Over the past several years, the development of novel and effective therapeutic agents for ARDS remains disappointing, and unfortunately, no recent therapeutic interventions have demonstrated a clear benefit. Herein, the results of several of these early and late phase clinical trials are reviewed, the majority of which address known maladaptive processes that have been deemed critical in ARDS pathophysiology. Based on the ongoing futility of current therapeutic models to yield effective therapies, it is speculated whether or not novel treatment paradigms, which address distinctly different aspects of this disease paradigm, may be warranted.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.170
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.027
GPT teacher head0.339
Teacher spread0.312 · 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
GenreCommentary

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

Citations46
Published2012
Admission routes1
Has abstractyes

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