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Record W7135885897

Topical Issues of the Regulation of International Air Carriage

2015· dissertation· cs· W7135885897 on OpenAlexaboutno aff
Anna Zubrová

Bibliographic record

VenueDigital Repository (National Repository of Grey Literature) · 2015
Typedissertation
Languagecs
FieldSocial Sciences
TopicInternational Law and Aviation
Canadian institutionsnot available
Fundersnot available
KeywordsConventionCarriageAviation lawCivil aviationInternational lawAir transport
DOInot available

Abstract

fetched live from OpenAlex

Resumé The thesis titled "Topical Issues of the Regulation of International Air Carriage" concerns itself with legal regulation germane to operating the international carriage by air. It is focused on carriage of cargo; carriage of passengers is only marginally mentioned. In the first chapter the author of the thesis defines the term of transport, transport law and compares the advantages and disadvantages of the means of transport in connection with the carriage of cargo. The second chapter of the thesis deals with the term of aviation law, historical development of the air transport and introduces the most important international organizations in the field of the civil air transport. The third chapter is dedicated to the historical development of the legal regulation in the field of the civil air transport, mainly the international legal regulation carried out by the Montreal Convention and the Warsaw Convention (with its amendments). This chapter also deals with the legal regulation of the European Union and analyses some selected EU regulations and describes national laws (mainly Civil Aviation Act). In this chapter there is also included the analysis of sources of the legal regulation and their mutual relations. It also explains the basics of the methods of regulation in the international private law -...

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)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.018
Threshold uncertainty score0.060

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0030.006
Scholarly communication0.0090.004
Open science0.0010.002
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0180.004

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 head0.286
Teacher spread0.277 · 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 designNot applicable
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

Citations0
Published2015
Admission routes1
Has abstractyes

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