MétaCan
Menu
Back to cohort
Record W2407730072 · doi:10.1186/2197-425x-3-s1-a999

CAN THEORETICAL VALUES FOR CHEST WALL COMPLIANCE BE USED IN ARDS PATIENTS?

2015· article· en· W2407730072 on OpenAlexaff
GQ Chen, M Xu, XL Chen, Nuttapol Rittayamai, Minsuok Kim, Ivo W. Soliman, Y-L Yang, Zhou Jx, Laurent Brochard

Bibliographic record

VenueIntensive Care Medicine Experimental · 2015
Typearticle
Languageen
FieldMedicine
TopicRespiratory Support and Mechanisms
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsMedicineARDSCompliance (psychology)Intensive care medicineCardiologyEmergency medicineInternal medicineLung

Abstract

fetched live from OpenAlex

To understand the impact of respiratory mechanics during mechanical ventilation, it is helpful to partition between the lungs and the chest wall. Esophageal pressure (Pes) is used to calculate chest wall compliance. However, esophageal pressure is not always used in the clinical arena. The value of chest wall compliance has been proposed to be estimated using 4% of the predicted value of vital capacity (VC) [ 1 ].

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)0.008
metaresearch head score (Gemma)0.058
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.058
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0040.003
Open science0.0030.001
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0040.003

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 head0.089
GPT teacher head0.372
Teacher spread0.283 · 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

Citations4
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueIntensive Care Medicine ExperimentalSame topicRespiratory Support and MechanismsFrench-language works237,207