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Record W4391654302 · doi:10.55905/oelv22n2-038

Analysis of barriers related to the costs incident about the cargo transportation by cabotage

2024· article· en· W4391654302 on OpenAlexaff
Evanilton de Almeida Vivaldo, Aldery Silveira Júnior

Bibliographic record

VenueOBSERVATÓRIO DE LA ECONOMÍA LATINOAMERICANA · 2024
Typearticle
Languageen
FieldEngineering
TopicMarine and Coastal Research
Canadian institutionsMinistère des Transports
Fundersnot available
KeywordsBusiness

Abstract

fetched live from OpenAlex

Cabotage in Brazil, despite offering cost reductions for the transportation of large cargo quantities, has been underutilized. The country boasts an extensive coastline and a demographic distribution favorable to the use of coastal shipping as a means of cargo transportation. The research aimed to identify the main barriers related to costs affecting coastal shipping in Brazil. The methodology relied on bibliographic and documentary research, encompassing books, journals, official documents, reports, as well as government websites. Five barriers were identified: Barriers related to fleet depreciation and renewal costs; Operational cost barriers; Capacity-related costs of vessels; Initial kilometer cost barriers; and Intermodality cost barriers. The conducted study could contribute to enhancing decision-making regarding cargo transportation in the country, while also encouraging investment decisions and promoting coastal shipping.

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)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.049
Threshold uncertainty score0.097

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.006
GPT teacher head0.246
Teacher spread0.240 · 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 designObservational
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 routes1
Has abstractyes

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