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Record W2890606929 · doi:10.1155/2018/3854090

Structural Analysis of Shipping Fleet Capacity

2018· article· en· W2890606929 on OpenAlex
Lixian Fan, Sijie Zhang, Jingbo Yin

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.

venuePublished in a venue whose home country is Canada.
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

VenueJournal of Advanced Transportation · 2018
Typearticle
Languageen
FieldEngineering
TopicMaritime Ports and Logistics
Canadian institutionsnot available
FundersNational Office for Philosophy and Social SciencesNational Natural Science Foundation of China
KeywordsDemolitionInvestment (military)Container (type theory)BusinessSupply and demandInvestment decisionsIndustrial organizationFinanceEconomicsMicroeconomicsEngineering

Abstract

fetched live from OpenAlex

With the unprecedented growth of the shipping transportation demand, substantial vessels have been built and delivered to the market. This has led to oversupply after the financial crisis in 2008 because of the abrupt decrease in transportation demand. Notwithstanding the importance of shipping market studies in the investment decision-making, there are relatively few empirical studies modelling the impacts on the structural changes of the fleet supply variables. By considering new orders, current fleet size, and demolitions in ship capacity supply, this study develops a systematic model in both bulker and container markets. The three-stage least squares method is employed to estimate the model to avoid endogenous issues. The primary finding suggests the significant impact of market, cost, and operational factors on fleet capacity supply. It also reveals the relatively rational activities in ordering new vessels and cautious in demolition decisions in the container market because of the large capital investment required. These are relevant to investment and demolition decisions in both the bulker and container markets.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.961
Threshold uncertainty score0.234

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 head0.239
Teacher spread0.224 · 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