MétaCan
Menu
Back to cohort
Record W7084103369 · doi:10.64799/jaoam.v3.i2.1

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

2024· article· en· W7084103369 on OpenAlexaff

Bibliographic record

VenueJournal of Airline Operations and Aviation Management · 2024
Typearticle
Languageen
FieldPsychology
TopicPrimate Behavior and Ecology
Canadian institutionsBoeing (Canada)
Fundersnot available
KeywordsCrewCivil aviationAviationCrew resource managementAviation engineeringAviation accidentResource (disambiguation)

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.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.940
Threshold uncertainty score0.242

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 head0.010
GPT teacher head0.312
Teacher spread0.301 · 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.

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

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Airline Operations and Aviation ManagementSame topicPrimate Behavior and EcologyFrench-language works237,207