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Record W4395016150 · doi:10.1007/978-3-031-52994-8

Air Navigation

2024· book· en· W4395016150 on OpenAlexaboutno aff
Octavian Thor Pleter

Bibliographic record

VenueSpringer aerospace technology · 2024
Typebook
Languageen
FieldSocial Sciences
TopicInternational Law and Aviation
Canadian institutionsnot available
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

This book took 30 years to write, so it is my only shot.Some of the drawings use airplanes which do not even fly anymore.If aviation were less reluctant to change, this would be worrying.But the value in aviation is expressed in billions of safe flight hours, so old ideas are not that bad.My oldest memories are about loving airplanes and the magic of flying.Much later, in high school I started wondering where they are going and how do they know.Now I am even more fascinated with this universe than in the beginning because I discovered that aviation is not only about aircraft but also about a very special kind of people.Living and working with them is a unique privilege.Clin Rovinescu, ex-CEO of Air Canada, describes the aviation community as dedicated people with two special traits: courage and intolerance to mediocrity.I was fortunate to have many students with a high degree of such intolerance.Now they are accomplished professionals.I also met exceptional pilots and instructors at the Romanian Airclub and Romanian Aviation Academy.This book represents my professional statement after 30+ years.Working with my aerospace engineering students, pilot students, and air traffic controller students over many generations has been challenging in the best possible way.Debates, ideas, and questions in the classroom were very productive in setting the contents.The text is split into three parts.The first presents the basics of space and time positioning in the Earth's atmosphere.The second part is an analysis of the air navigation systems and other onboard systems relevant to the flight trajectory.The third part focuses on flight trajectory planning, management, and optimisation.Chapter 12 on Air Traffic Management was written by Razvan Margauan, Head of Technical Systems at EUROCONTROL Maastricht UAC, my role as co-author being marginal.This decision to let him take the lead reflects my concern about my 30 years old professional bias on the subject.It is in the best interest of the reader to be cautioned on this bias of mine when it comes to full automation of Air Traffic Management.In contrast, Chap.11 remains fully biased, under the alibi of presenting future ideas in air navigation.Rzvan added the required equilibrium and objectivity on the ATM subject in Chap.12, together with his solid knowledge and hands-on experience.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.749
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.010
GPT teacher head0.285
Teacher spread0.275 · 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 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

Citations4
Published2024
Admission routes1
Has abstractyes

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