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Record W1797092671

Odgovornost za štete prouzročene zloupotrebom zrakoplova

2008· article· sl· W1797092671 on OpenAlexaboutno aff
Maja Bukovac Puvača, Sandra Debeljak-Rukavina

Bibliographic record

VenueCollected Papers of Zagreb Law Faculty · 2008
Typearticle
Languagesl
FieldSocial Sciences
TopicInternational Law and Aviation
Canadian institutionsnot available
Fundersnot available
KeywordsDamagesLiabilityConventionLawCompensation (psychology)Strict liabilityPolitical scienceTortTerrorismBusinessPsychology
DOInot available

Abstract

fetched live from OpenAlex

In this paper, the authors analyse non-contractual and contractual liabilities for damages caused by the misuse of aircraft. They also give an overview of the Rules of the Rome Convention and the Montreal Protocol laying down liability for the damages caused by a foreign aircraft to third persons on the ground, and the main indications of efforts to modernise these Rules. These solutions at the international level are compared with those contained in the national legislations, as well as in domestic and comparative law. Special emphasis is put on the way the United States of America has solved the issue of compensation for damages to the victims of the terrorist attack of 11 September 2001. The contractual liability for damages caused by the misuse of aircraft in international air traffic is regulated by the Montreal Convention of 1991, whose provisions are compared with those contained in the national law of Croatia. A conclusion is drawn that in the case of the misuse of aircraft, such as on 11 September, the focus is transferred from the problem of liability as such, i.e. from an effort to identify the persons, apart from the perpetrators themselves, who may also be responsible for the damage caused, to the problem of how to compensate the victims in a fast and just way, at least for the damages resulting in death or various bodily injuries.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.021
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0020.002
Scholarly communication0.0060.003
Open science0.0000.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0210.004

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 head0.037
GPT teacher head0.287
Teacher spread0.250 · 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
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
Published2008
Admission routes1
Has abstractyes

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