British Columbia : innovation, capital and carbon : Vancouver workshop findings report
Bibliographic record
Abstract
British Columbia (BC) has some of the most aggressive greenhouse gas (GHG) reduction targets in the world. The 2007 Greenhouse Gas Reduction Targets Act (GGRTA) establishes a commitment to reduce provincial emissions 33% below 2007 levels. The Carbon Governance Project workshop: Innovation, Capital and Carbon, took place in Vancouver, BC on June 1st, 2011. The workshop brought together 48 leading industry experts, scholars and government representatives to focus on understanding factors that enable and constrain the transformation to a low carbon economy in British Columbia (BC). This document summarizes the results of the workshop, focusing on the low carbon landscape in BC, and describes the key strategies identified by the participants for advancing the low carbon economy. The summary is based on materials generated during the day and results from voting by the participants to identify priorities. CGP international workshop series
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.008 | 0.001 |
| Scholarly communication | 0.009 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.050 | 0.010 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".