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Record W4245588325 · doi:10.32920/ryerson.14655192

Commuting for work and neighbourhood energy consumption

2021· preprint· en· W4245588325 on OpenAlexaboutno aff
Dil Rowshan

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicUrban Transport and Accessibility
Canadian institutionsnot available
Fundersnot available
KeywordsTRIPS architectureNeighbourhood (mathematics)Work (physics)Energy consumptionTransport engineeringPlan (archaeology)Consumption (sociology)Greenhouse gasBusinessGeographyEngineeringSociology

Abstract

fetched live from OpenAlex

This study aimed to explore the impact of the Places to Grow Plan 2006 on travel behavior of the work commuters living in GTHA. A comparative analysis was done between the year 2001 and 2011 which represent the situations five year before and after the implementation of the Plan. Data were collected from Transportation Tomorrow Survey. The study revealed that in 2011, energy consumption by motorized vehicles increased in the Traffic Assessment Zones of GTHA around the Growth Centres designated by the Places to Grow Plan. Active transportation increased mainly in Toronto in 2011. It is apprehended that the intensification strategy of the Places to Grow Plan contributed in increasing the energy consumption of work commuters either by increasing the number of trips or length of trips made by motorized vehicles (including cars and different forms of transit) which also affect the Greenhouse Gas emissions in the atmosphere.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.030
Threshold uncertainty score0.060

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.054
GPT teacher head0.328
Teacher spread0.274 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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