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Record W4383823826 · doi:10.11159/iccste23.210

Maritime Transport Infrastructure Effects on the Territory Development

2023· article· en· W4383823826 on OpenAlexvenueno aff
Hanan Kaffoura, Ossama Khalil

Bibliographic record

VenueProceedings of the International Conference on Civil, Structural and Transportation Engineering · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicArctic and Russian Policy Studies
Canadian institutionsnot available
Fundersnot available
KeywordsTransport infrastructureComputer scienceBusinessTransport engineeringEngineering

Abstract

fetched live from OpenAlex

The Port represents the main Maritime Transport Infrastructure which has suffered developments and changes of use, often with negative effects on the urban development of the surrounding territory, losing the original morphology, authenticity and integrity of the relationship between the land and the sea. In recent years, with the development of society, people's awareness of environmental protection has increased, although the Port promotes economic development and employment levels. For this reason, the local authorities and the local communities have started to analyse and study solutions to solve these negative impacts, following the international standards of international organizations. In this contribution we present the situation of the development of the commercial port in relation to the surrounding territory through a case study concerning the port of Lattakia in Syria, reflecting three trends: the first is the great changes and continuous challenges that the Port faces today; the second concerns the enhancement and analysis of the maritime and terrestrial fabric; the last is the role of the ecological transition in sustainable development in finding solutions respectful of the environment and in favour of the society that uses it, with the aim of safeguarding the original identity of the relationship between the land and the sea, offering more social spaces of relationship and less transport traffic within the area connected between the sea and the city.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.946
Threshold uncertainty score0.276

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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.015
GPT teacher head0.245
Teacher spread0.231 · 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.

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
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the International Conference on Civil, Structural and Transportation EngineeringSame topicArctic and Russian Policy StudiesFrench-language works237,207