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Record W2561266946 · doi:10.4000/echogeo.14807

L’Alaska Railroad Corporation : un modèle ferroviaire original aux confins des États-Unis entre diversification commerciale et stratégie touristique intégrée

2016· article· fr· W2561266946 on OpenAlexaff
Matthieu Schorung

Bibliographic record

VenueEchoGéo · 2016
Typearticle
Languagefr
FieldEngineering
TopicMaritime Ports and Logistics
Canadian institutionsCanadian Water and Wastewater Association
Fundersnot available
KeywordsHumanitiesPolitical scienceGeographyArt

Abstract

fetched live from OpenAlex

L’Alaska Railroad Corporation (ARRC) constitue un modèle ferroviaire unique aux États-Unis : compagnie publique détenue par l’État de l’Alaska, unité des services de fret et de passagers, stratégie financière diversifiée. Le chemin de fer a permis l’ouverture au peuplement et à l’exploitation de l’Alaska. Ce mode de transport est aujourd’hui un acteur majeur de son système de transport. Par ailleurs, sa stratégie touristique fait de l’ARRC un acteur à part entière de la mise en tourisme et de la valorisation de l’Alaska. Il s’agit, à travers cet article, d’analyser les caractéristiques propres à cette compagnie et les fondements de sa réussite, et de considérer la stratégie de l’ARRC comme un facteur structurant des dynamiques économiques et territoriales actuelles de l’Alaska.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.098
Threshold uncertainty score0.194

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0170.001

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 head0.046
GPT teacher head0.259
Teacher spread0.213 · 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 designQualitative
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

Citations1
Published2016
Admission routes1
Has abstractyes

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