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How much should transmission facility owners be compensated for wildfire mitigation?

2022· article· en· W4312896340 on OpenAlexaffabout
Joanne G. Phillips, Dan J. Levson, Calvin D. Baynes

Bibliographic record

Venue2022 IEEE Power & Energy Society General Meeting (PESGM) · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Conservation and Criminology Analyses
Canadian institutionsBAH Enterprises (Canada)
Fundersnot available
KeywordsTransmission (telecommunications)Computer scienceBusinessTelecommunications

Abstract

fetched live from OpenAlex

Separate funds are increasingly being requested for wildfire mitigation plans (WMPs) whose activities were previously managed within a transmission facility owner's (TFO's) capital and operating budgets. Experience from a regulatory proceeding where a TFO in Alberta, Canada, sought approval of just over Can$26.2 million for its WMP is presented. The TFO expressed concern that wildfire risk is increasing due to a warming climate in Alberta and submitted that “the frequency and severity of fires and extreme weather events in Alberta is increasing.” The Consumers' Coalition of Alberta, intervening in the proceeding, argued that the funding the TFO was requesting was too high given the relatively low risk transmission lines present to initiate wildfires. A summary of the arguments is presented and the necessity to devise some method to evaluate a public risk acceptability level in a cost benefit analysis and to obtain critical wildfire risk mitigation information is discussed.11Bema Enterprises Ltd. prepared evidence for the Consumers' Coalition of Alberta in Alberta Utilities Commission proceedings 23848 and 26509.

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)0.011
metaresearch head score (Gemma)0.055
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.059
Threshold uncertainty score0.142

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.055
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0020.002
Scholarly communication0.0060.007
Open science0.0020.001
Research integrity0.0090.005
Insufficient payload (model declined to judge)0.0430.003

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 head0.059
GPT teacher head0.279
Teacher spread0.220 · 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 designTheoretical or conceptual
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

Citations1
Published2022
Admission routes2
Has abstractyes

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Same venue2022 IEEE Power & Energy Society General Meeting (PESGM)Same topicWildlife Conservation and Criminology AnalysesFrench-language works237,207