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Record W2227258180

Healing the Planet: GIS Helps British Columbia Respond to Climate Change with Climate Action

2014· article· en· W2227258180 on OpenAlexaboutno aff
Benjamin Y. Clark

Bibliographic record

VenueWestern CEDAR (Western Washington University) · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicGeographic Information Systems Studies
Canadian institutionsnot available
Fundersnot available
KeywordsClimate changeAction (physics)GeographyEnvironmental resource managementEnvironmental scienceGeologyOceanography
DOInot available

Abstract

fetched live from OpenAlex

The Community Energy and Emissions Inventory (CEEI) represents over 200 individual reports of energy consumption and greenhouse gas emissions. The data is split into on-road transportation, buildings, solid waste, deforestation and agriculture. A first of its kind inventory in North America, it enables local governments to meet the BC Climate Action Charter commitment to measure and report on their green house gas (GHG) emissions profiles. Making the data available in a GIS map-based format at large scales assists local governments in making effective policies and actions towards reducing GHGs and creating compact, complete energy efficient communities. Outputs of the inventory and contributing spatial analysis allow more easy integration with GHG modeling and local planning processes that are spatially driven. This paper overviews and describe the challenges and success of how GIS is supporting this critical program for climate action in British Columbia.

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)0.003
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.103
Threshold uncertainty score0.206

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0080.005
Scholarly communication0.0090.003
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0130.002

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 head0.033
GPT teacher head0.254
Teacher spread0.221 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2014
Admission routes1
Has abstractyes

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