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Record W1963996745 · doi:10.7227/tjth.24.1.3

Ore Imports and Port Competition

2003· article· en· W1963996745 on OpenAlexaff
Daniel Todd

Bibliographic record

VenueThe Journal of Transport History · 2003
Typearticle
Languageen
FieldEngineering
TopicMaritime Ports and Logistics
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsPort (circuit theory)Competition (biology)BusinessIndustrial organizationInternational tradeCommerceEngineeringEcology

Abstract

fetched live from OpenAlex

Competition between neighboring ports to serve the same hinterland customers is often decided on the suitability of the infrastructure offered by the ports. Infrastructure is not fixed in time; provision of it can change, altering the competitive advantage of ports. This was the case with iron ore imports into west Cumberland (England), with bulk cargos requiring specialized facilities in the form of enclosed docks. First Maryport, and then Workington, gained precedence on the strength of their commitment to dock infrastructure. In this paper, the ramifications of the trade for Cumberland ports are examined over an extended period beginning with the first imports in the 1870s.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.023
Threshold uncertainty score0.077

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0030.005
Scholarly communication0.0050.004
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0230.001

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 head0.010
GPT teacher head0.171
Teacher spread0.160 · 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 source (direct Gemma or distilled Codex), 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

Citations2
Published2003
Admission routes1
Has abstractyes

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