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Adaptation planning of container ports in the context of typhoon risks: The case of Ningbo-Zhoushan port in China

2024· article· en· W4401386120 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueOcean & Coastal Management · 2024
Typearticle
Languageen
FieldEngineering
TopicMaritime Ports and Logistics
Canadian institutionsUniversity of Manitoba
FundersNingbo Municipal People's GovernmentNational Natural Science Foundation of China
KeywordsTyphoonPort (circuit theory)ChinaAdaptation (eye)Container (type theory)Context (archaeology)Environmental resource managementGeographyEnvironmental protectionEnvironmental scienceMeteorologyEngineeringBiologyArchaeology

Abstract

fetched live from OpenAlex

This study conducts a comprehensive survey of the risk of typhoon to container ports by assessing the risk level of typhoons in China's major container ports, predicting their economic losses, and evaluating corresponding adaptation measures. It analyzes adaptation measures in response to typhoon impacts, with a case study of Ningbo-Zhoushan port, one of China's most representative regional ports. It identifies the inadequate supply of institutions and the absence and misbehavior of the main port stakeholders as the main cause of varying institutional imperfections in the port adaptation system. This study contributes to the development of efficient port typhoon prevention policies, reduction of economic losses and casualties, and improvement of port operational efficiency. It also fills an important research gap on climate risk and adaptation in China's container ports, with an emphasis in enhancing port resilience.

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.

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)0.001
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.268
Threshold uncertainty score0.328

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.021
GPT teacher head0.251
Teacher spread0.230 · 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