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Record W3212908210 · doi:10.5957/icetech-2010-101

Canadian Arctic Shipping and Emission Assessment

2010· article· en· W3212908210 on OpenAlexaffabout
Ernst Radloff, Bohdan Hrebenyk

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicMaritime Transport Emissions and Efficiency
Canadian institutionsTransport Canada
Fundersnot available
KeywordsArcticEnvironmental scienceBaseline (sea)The arcticGreenhouse gasPopulationEmission inventoryClimate changeEnvironmental protectionOceanographyMeteorologyGeographyAir quality index

Abstract

fetched live from OpenAlex

The changing Arctic environment is a significant consideration in the forecast of future marine emissions stemming from the potential increase in natural resource extraction and inter-and intra-Arctic shipping. The Transport Development Centre (TDC) of Transport Canada has carried out a vessel emission inventory study for marine vessels operating in the Canadian Arctic. The inventory comprises a baseline assessment for the years 2002 to 2007 and forecasts to 2010, 2020, and 2050. The inventory utilizes a “bottom-up” vessel activity based approach consistent with current best practices and was completed using the marine emission inventory tool (MEIT). The forecasts were based on expected population growth, and economic activities in the Arctic. Also taken into consideration are the changes and projections for the Arctic environment, specifically when and to what extent the ice will recede allowing for increased vessel access to the Arctic. The forecast shows that by 2050 a significant increase in Green-house gas (GHG) and emissions are expected to occur due to an increase in intra-Arctic shipping resource extraction and eco-tourism. This translates into a five-fold increase for both CO2 and NOx and significant increases in other criteria air contaminants (CAC) especially if large-scale gas production occurs in the western arctic region of Canada. The forecast also includes several scenarios such as the designation of the Arctic as an Emission Control Area (ECA) and the harmonization with EPA and IMO Marpol regulations for marine fuel and engine emission standards, which would have the potential to lower CAC emissions.

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 score0.260
Threshold uncertainty score0.962

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)0.0390.000

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 head0.004
GPT teacher head0.218
Teacher spread0.214 · 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

Citations0
Published2010
Admission routes2
Has abstractyes

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