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Record W2588128515 · doi:10.4324/9781315739618-17

Air cargo transport and logistics in Hong Kong and Southern China

2018· book-chapter· en· W2588128515 on OpenAlexaff
Yulai Wan, Anming Zhang

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldEconomics, Econometrics and Finance
TopicAviation Industry Analysis and Trends
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsChinaAir cargoBusinessAir transportGeographyAeronauticsTransport engineeringEngineeringArchaeology

Abstract

fetched live from OpenAlex

Based on Hong Kong’s air-borne trade pattern since 2000, this chapter reveals the increasing importance of Mainland China in Hong Kong’s air cargo business. Hong Kong plays a significant role as a gateway to southern China. However, after the 2008 financial crisis, a number of factors raised the dynamics of the air cargo business in Hong Kong. Since then, demand for air cargo service in Hong Kong has become more sensitive to freight rate and income than before. In addition to the deteriorating global economic environment, both regulation and policy changes in China and competition from airports in Mainland China contribute to this change. Despite these new developments, Hong Kong has managed to keep its competitive edge in the air cargo business, mainly owing to its free port status, strategic positioning, efficient customs clearance, strong international connectivity, and great special cargo handling skills.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.572
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0030.000

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 head0.032
GPT teacher head0.197
Teacher spread0.165 · 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.

Study designTheoretical or conceptual
Domainnot available
GenreOther

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

Citations5
Published2018
Admission routes1
Has abstractyes

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