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Record W3214959027 · doi:10.3390/en14237925

Design and Implementation of an Electric Skibus Line in North Italy

2021· article· en· W3214959027 on OpenAlexaff
Carola Leone, Laura Sturaro, Giacomo Geroli, Michela Longo, Wahiba Yaïci

Bibliographic record

VenueEnergies · 2021
Typearticle
Languageen
FieldEngineering
TopicAdvanced Battery Technologies Research
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsElectrificationWork (physics)Context (archaeology)Line (geometry)Service (business)Transport engineeringPlan (archaeology)Automotive engineeringElectric energyDiesel fuelPublic transportEnvironmental economicsEnvironmental scienceEngineeringBusinessElectricityElectrical engineeringGeographyEconomicsMechanical engineeringMarketing

Abstract

fetched live from OpenAlex

To enhance the current Public Transport (PT) service in the northern Italian region of Lombardy, this work tries to plan fully a new electric Skibus line connecting the cities of Santa Caterina and Livigno. As a first try outside the city environment, the electrification study is set on a limited mountain zone hence featured by steep grades and cold temperatures. In the first part of the paper, the energy consumed by an electric bus working in such a context is assessed, and from the learned outcomes, proper charging infrastructure is proposed. From the found results, the introduction of a new electric bus line in the chosen region seems feasible. Finally, in the last part of the work the performances of an electric bus fleet are compared with that of a diesel one, in terms of fuel costs and Well-to-Wheel (WTW) emissions. The results prove that an electric fleet would be more convenient for both the economic and the environmental aspects.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

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 communication0.0010.000
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0070.002

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 head0.014
GPT teacher head0.285
Teacher spread0.271 · 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 designBench or experimental
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

Citations4
Published2021
Admission routes1
Has abstractyes

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