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Record W2523111472 · doi:10.5603/ait.a2016.0038

High frequency oscillatory ventilation for adult ARDS: Is this the end of the road?

2016· article· en· W2523111472 on OpenAlexaboutno aff
Mohan Gurjar, Arvind Baronia

Bibliographic record

VenueAnaesthesiology Intensive Therapy · 2016
Typearticle
Languageen
FieldMedicine
TopicRespiratory Support and Mechanisms
Canadian institutionsnot available
Fundersnot available
KeywordsARDSMedicineVentilation (architecture)High-frequency ventilationIntensive careMechanical ventilationPositive end-expiratory pressureAnesthesiaIntensive care medicineLungInternal medicinePhysics

Abstract

fetched live from OpenAlex

ENWEndNote BIBJabRef, Mendeley RISPapers, Reference Manager, RefWorks, Zotero AMA Gurjar M, Baronia AK. High frequency oscillatory ventilation for adult ARDS: Is this the end of the road?. Anaesthesiology Intensive Therapy. 2016;48(4). APA Gurjar, M., & Baronia, A. K. (2016). High frequency oscillatory ventilation for adult ARDS: Is this the end of the road?. Anaesthesiology Intensive Therapy, 48(4). Chicago Gurjar, Mohan, and Arvind K Baronia. 2016. "High frequency oscillatory ventilation for adult ARDS: Is this the end of the road?". Anaesthesiology Intensive Therapy 48 (4). Harvard Gurjar, M., and Baronia, A. (2016). High frequency oscillatory ventilation for adult ARDS: Is this the end of the road?. Anaesthesiology Intensive Therapy, 48(4). MLA Gurjar, Mohan et al. "High frequency oscillatory ventilation for adult ARDS: Is this the end of the road?." Anaesthesiology Intensive Therapy, vol. 48, no. 4, 2016. Vancouver Gurjar M, Baronia A. High frequency oscillatory ventilation for adult ARDS: Is this the end of the road?. Anaesthesiology Intensive Therapy. 2016;48(4).

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)0.003
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation 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: Commentary · Consensus signal: none
Teacher disagreement score0.082
Threshold uncertainty score0.275

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.012
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0040.004
Open science0.0010.001
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0820.046

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 head0.025
GPT teacher head0.270
Teacher spread0.245 · 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 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".

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Citations0
Published2016
Admission routes1
Has abstractyes

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