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Record W826737116 · doi:10.69554/dasj2480

Environmental management planning: A Canadian perspective

2008· article· en· W826737116 on OpenAlexaboutno aff
Alec W.M. Simpson

Bibliographic record

VenueJournal of airport management · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental and Social Impact Assessments
Canadian institutionsnot available
Fundersnot available
KeywordsPerspective (graphical)Environmental planningBusinessEnvironmental resource managementGeographyComputer scienceEnvironmental scienceArtificial intelligence

Abstract

fetched live from OpenAlex

The aviation industry has faced significant economic and environmental challenges over the past 20 years. Increased public concern regarding protection of the environment from the impacts of transportation has prompted governments to seek voluntary and regulatory measures to manage the various modes of transportation. Canada, as a global partner, has responded to the challenges of airport environmental management with a balanced approach between voluntary and regulatory measures. Through the development of environmental management plans and procedures, airports and carriers have been able to reduce negative impacts on air, water and soil and respond to challenges concerning aircraft de-icing fluids, greenhouse gases (GHGs) and other air emissions. This paper provides an overview of environmental issues facing the Canadian Government and aviation industry, management procedures utilised to manage these issues, and environmental management challenges of the future. It will focus on examples of a water quality issue through the management of de-icing fluids. It will also provide an overview of the management of GHGs and air pollutants through a voluntary agreement.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.258
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 communication0.0000.000
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 head0.013
GPT teacher head0.244
Teacher spread0.232 · 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.

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

Citations2
Published2008
Admission routes1
Has abstractyes

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