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Record W4235393386 · doi:10.1201/9781003151326-6

New Brunswick

2020· book-chapter· en· W4235393386 on OpenAlexaboutno aff
Pierre Langlois, Geneviève Gauthier

Bibliographic record

VenueRiver Publishers eBooks · 2020
Typebook-chapter
Languageen
FieldEnvironmental Science
TopicSustainable Development and Policies
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical science

Abstract

fetched live from OpenAlex

New Brunswick energy consumption decreased by 18% from 1995 to 2015, mostly due to a 21% decline during the 2010-2015 period. In 2005, the Energy Efficiency and Conservation Agency of New Brunswick was established as a Crown Corporation to act as the primary organization for the promotion of EE and conservation in NB. The EE strategy for the province, White Paper on NB Energy Policy, was released in 2000 and established an energy policy framework up to 2010. The energy policy had the following goals: Another important document for EE and energy conservation in NB is the New Brunswick Energy Blueprint released in 2011, a long-term vision and a strategic action plan for the sector. In response to the actions in the NB Energy Blueprint, a certification program was launched called Energy Fundamentals for Leaders at the University of New Brunswick Saint John Campus.

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 categoriesInsufficient payload (model declined to judge)
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 score0.635
Threshold uncertainty score0.983

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.007
Science and technology studies0.0040.001
Scholarly communication0.0080.004
Open science0.0020.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.3110.139

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 head0.012
GPT teacher head0.188
Teacher spread0.176 · 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.

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
Published2020
Admission routes1
Has abstractyes

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