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Record W4220734099 · doi:10.5281/zenodo.6303446

Toward single pilot operations: A conceptual framework to manage in-flight incapacitation

2022· paratext· en· W4220734099 on OpenAlexaff
Ana Paz Goncalves Martins, Teemu Joonas Lieb, Max Friedrich, Stefano Bonelli, Marcello Celori, Aurora De Bortoli Vizioli, Giuseppe Contissa, Francesco Godano, Galileo Sartor, Laurence Rognin, Supathida Boonsong, Martin Christiansson, Pasquale Capasso, Ricardo JN Reis, José Ricardo Parizi Negrão, Andreas Triska

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2022
Typeparatext
Languageen
FieldEngineering
TopicAerospace and Aviation Technology
Canadian institutionsDeep River Science Academy
FundersEuropean Commission
KeywordsComputer scienceConceptual designAeronauticsSystems engineeringEngineeringHuman–computer interaction

Abstract

fetched live from OpenAlex

A major challenge for the implementation of Single Pilot Operations (SPO) in commercial aviation is how to deal with the potential risk of in-flight pilot incapacitation. In this paper, a conceptual framework is presented aiming at supporting flight and landing of a single-piloted aircraft in case the single pilot on board becomes incapacitated during the flight, specifically focusing on the ground side of the Air Traffic Management (ATM) framework. This concept considers the interaction of a groundbased pilot operating through a remote cockpit position with onboard automation and air traffic controllers. A description of the foreseen operational processes and procedures allowing the transition from single-piloted aircraft to Remotely Piloted Aircraft (RPA) is provided, together with an analysis of their technical, legal, and regulatory implications.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0030.011
Scholarly communication0.0090.010
Open science0.0040.005
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.0060.002

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 head0.044
GPT teacher head0.244
Teacher spread0.200 · 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 designTheoretical or conceptual
Domainnot available
GenreOther

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

Citations6
Published2022
Admission routes1
Has abstractyes

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