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Record W4403836139 · doi:10.1155/2024/9190221

Western North American Cruise Shipping Network: Space Structure and System

2024· article· en· W4403836139 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueComplexity · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicCruise Tourism Development and Management
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsCruiseSpace (punctuation)Network structureComputer scienceAeronauticsGeologyOceanographyEngineeringDistributed computing

Abstract

fetched live from OpenAlex

Regionalization is the basic feature of cruise shipping network organization. We insist that the cruise networks of Alaska, Hawaii, etc., have developed into a whole with the scaling up of cruise tourism. To prove it, we used complex network analysis methods to explore the port connections and the spatial structure of the cruise shipping network in these regions. We found that Alaska, Hawaii, and the west coast of Mexico all belong to seasonal cruise market areas. Cruise itineraries in these areas are categorized into one‐way and round‐trip itineraries, and more than 70% of the itineraries are short duration and medium duration. These areas build cruise shipping networks used in Vancouver, Los Angeles, Anchorage, San Francisco, Honolulu, and other cruise ports, which can be subdivided into nine single‐core cruise shipping network systems and two dual‐core cruise shipping network systems. The interconnection of different systems forms a T‐shaped cruise shipping network in geographical space.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.334
Threshold uncertainty score0.909

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 head0.046
GPT teacher head0.302
Teacher spread0.256 · 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