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Toward Sustainable Trucking:

2013· article· en· W3084227557 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueTransportation Journal · 2013
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicRegulation and Compliance Studies
Canadian institutionsManitoba Beekeepers' AssociationUniversity of Manitoba
Fundersnot available
KeywordsTonnageTruckTrucking industryInvestment (military)BusinessSustainable transportCapital investmentFuel efficiencyTransport engineeringConsumption (sociology)EngineeringSustainabilityFinance

Abstract

fetched live from OpenAlex

Abstract A trucking company president recently exclaimed: “Life is not trucking, but trucking is life.” Indeed, the goods that support North American lifestyles today are mostly delivered by trucks. Trucking also employs large numbers of people, burns billions of gallons of fuel, and produces tremendous tonnage of harmful emissions. This article combines the literature with lessons from green transportation leaders to identify four themes regarding movement toward sustainable trucking: (1) there are many ways to reduce emissions and fuel consumption; (2) many of these methods require substantial capital investment; (3) collaboration among the relevant stakeholders is needed to move forward; and (4) ultimately people—such as consumers, truck drivers, owner-operators, and taxpayers—will determine the future of trucking.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.548
Threshold uncertainty score0.999

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 communication0.0000.002
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.025
GPT teacher head0.219
Teacher spread0.194 · 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