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Record W6923388220 · doi:10.14288/1.0443918

The Economic Feasibility of (Re-)Introducing Tram-Trains in Canada: Okanagan Valley Electric Regional Passenger Rail

2024· article· en· W6923388220 on OpenAlexaboutno aff

Bibliographic record

VenueOpen Collections · 2024
Typearticle
Languageen
FieldEngineering
TopicVehicle emissions and performance
Canadian institutionsnot available
Fundersnot available
KeywordsTourismEconomic feasibilityPopulationService (business)Public transportEconomic impact analysisNet present valueTransit (satellite)Light rail transit

Abstract

fetched live from OpenAlex

Population and tourism growth has increased congestion, collisions, climate harming emissions, and transport inequities in the Okanagan Valley, British Columbia (B.C.), Canada. Surveys indicate a willingness among residents to switch from cars to public transit featuring better service levels and connections. We conducted an analysis on the economic feasibility of an Okanagan Valley Electric Regional Passenger Rail (OVER PR) powered by zero-emission (ZE) Fuel Cell/Battery Hybrid Rail (Hydrail) technology along a 342-km route between Osoyoos, B.C., at the US Border and Kamloops, B.C., the Canadian VIA rail hub. Hydrail passenger light-rail has operated successfully since 2018 in Germany and was demonstrated in Quebec, Canada, in 2023. Technical analyses have confirmed the feasibility in B.C. on steep Highway (Hwy) 97 grades and mountainous weather, with mode shift forecasts in the range of 30%. OVER PR economic analyses were also favorable, with net present value (NPV) = CAD 40 billion (CDN, base year 2023), benefit–cost ratio (BCR) = 9:1, and Return on Investments (IRR) = 33% over 30 years. Subject to additional stakeholder consultations and final design reviews, these results were tested against risks using Monte Carlo Simulation (MCS) and Reference-Class Forecasting (RCF), including worst-case risks such as 70% cost over-runs. OVER PR promises an economic transition to clean energy, sustainable transportation, and more livable communities, benefiting all Valley communities through greater transportation equity.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.537
Threshold uncertainty score0.388

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.021
GPT teacher head0.242
Teacher spread0.221 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations0
Published2024
Admission routes1
Has abstractyes

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