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Record W4404883519 · doi:10.69978/jaoam.v3.i2.1

THE IMPORTANCE AND EFFECTIVENESS OF CREW RESOURCE MANAGEMENT (CRM) IN RUSSIAN AVIATION

2024· article· en· W4404883519 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Airline Operations and Aviation Management · 2024
Typearticle
Languageen
FieldComputer Science
TopicEngineering Education and Technology
Canadian institutionsBoeing (Canada)
Fundersnot available
KeywordsCrew resource managementCrewAviationBusinessProcess managementOperations managementKnowledge managementEngineeringAeronauticsComputer scienceAerospace engineering

Abstract

fetched live from OpenAlex

The modern air transport system is characterized by a great dependence on humans and the safe functioning of all its elements is determined by the “human factor”, which plays a major role in the management and stability of the entire system. With the passage of time and the development of the aviation industry, the role of the human factor in aviation accidents has significantly increased and changed. This article is devoted to the need for effective management of the resources of the crew (cabin) of an aircraft, in particular, the formation of systematic knowledge about the basic requirements and features, ensuring the safe operation of civil aviation aircraft.

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.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.924
Threshold uncertainty score0.177

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0000.000

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 head0.004
GPT teacher head0.239
Teacher spread0.235 · 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