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Record W7026757218

Burden of proof reversion in aviation law. Disproportion of the burden of proof in air carriage contracts of passengers, baggage or cargo

2014· other· es· W7026757218 on OpenAlexaboutno aff

Bibliographic record

VenueRepositorio Institucional (Pontificia Universidad Javeriana) · 2014
Typeother
Languagees
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsAviationBurden of proofWork (physics)Carriage
DOInot available

Abstract

fetched live from OpenAlex

El presente escrito busca reflexionar sobre la carga de la prueba derivada del régimen de responsabilidad del transporte aéreo, tanto a nivel Internacional (Convenio de Montreal de 1999), como a nivel Nacional (Código de Comercio), en el entendido de que existen ciertas situaciones donde esta podría invertirse. Esto, debido a hechos desproporcionados y desequilibrados que se presentan en el ejercicio diario de la actividad aeronáutica. El escrito, tiene como método, una estrategia investigativa deductiva, razón por la cual se partió de una premisa general para llegar a una temática específica, “situaciones desproporcionadas o desequilibradas en el desarrollo de la actividad de transporte aéreo, donde se invierte la carga de la prueba”. En conclusión, el escrito propone la inversión de la carga de la prueba, en determinados casos donde resulta evidente la incongruencia, de acuerdo con el principio de economía procesal, tan importante en el ajetreado tránsito jurídico de la actualidad.

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)0.012
metaresearch head score (Gemma)0.043
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 score0.034
Threshold uncertainty score0.077

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.043
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0050.012
Scholarly communication0.0120.010
Open science0.0030.004
Research integrity0.0130.009
Insufficient payload (model declined to judge)0.0220.003

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 head0.009
GPT teacher head0.231
Teacher spread0.222 · 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
Published2014
Admission routes1
Has abstractyes

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