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Record W4401720105 · doi:10.4050/f-0080-2024-1331

The Canadian Vertical Lift Autonomy Demonstration Project – High Level Concepts for the Development of Autonomy

2024· article· en· W4401720105 on OpenAlexaffabout
Derek Gowanlock, Arthur Gubbels

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicTraffic control and management
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsAutonomyLift (data mining)Development (topology)Computer sciencePolitical scienceMathematics

Abstract

fetched live from OpenAlex

Through the development and flight testing of the Canadian Vertical Lift Autonomy Demonstration (CVLAD) Autonomous Flight System (AFS), the NRC has developed technical and operational insight into many high-level concepts of a full-scale supervised-autonomous helicopter, which are thought to be applicable to a wide variety of implementations and approaches. This paper presents two important concepts: "The Contract" and "Levels of Aggression", for which it is expected some aspect of implementation would be required in any supervised autonomous platform and in particular for platforms where the pilot supervising the autonomy remains on-board the aircraft (and thus the AFS provides a 'competent co-pilot' type functionality).

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)0.002
metaresearch head score (Gemma)0.001
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: Empirical · Consensus signal: none
Teacher disagreement score0.502
Threshold uncertainty score0.990

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.035
GPT teacher head0.264
Teacher spread0.229 · 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
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 routes2
Has abstractyes

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