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Record W2901624254 · doi:10.1136/heartjnl-2018-313059

Congenital heart disease in aircrew

2018· review· en· W2901624254 on OpenAlexaff
Edward Nicol, Olivier Manen, Norbert Guettler, Dennis Bron, Eddie D Davenport, Thomas Syburra, Gary Gray, Joanna d’Arcy, Rienk Rienks

Bibliographic record

VenueHeart · 2018
Typereview
Languageen
FieldMedicine
TopicCardiovascular and Diving-Related Complications
Canadian institutionsCanadian Armed Forces
Fundersnot available
KeywordsAircrewMedicineExpert opinionCivil aviationAviationAviation medicineAeronauticsMilitary aviationWork (physics)Medical emergencyIntensive care medicineEngineeringPathology

Abstract

fetched live from OpenAlex

with suspected or confirmed congenital heart disease (both pilots and non-pilot aviation professionals). It presents expert consensus opinion and associated recommendations and is part of a series of expert consensus documents covering all aspects of aviation cardiology. This expert opinion was born out of a 3 year collaborative working group between international military aviation cardiologists and aviation medicine specialists, as part of a North Atlantic Treaty Organization (NATO) led initiative to address the occupational ramifications of cardiovascular disease in aircrew (HFM-251) many of whom also work with and advise civil aviation authorities.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.485
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.003

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 head0.054
GPT teacher head0.350
Teacher spread0.296 · 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
GenreReview

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
Published2018
Admission routes1
Has abstractyes

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