Sharing Knowledge for a Better Future: Adaptation and Clean Energy Experiences in a Changing Climate
Bibliographic record
Abstract
We like to think of ourselves as Eco-Warriors, because we know that we have to go out and be assertive to get this message across.If we just do nothing, Mother Nature will show us where we've gone wrong."Chief Gordon Planes, T'Sou-ke First Nation T'Sou-ke First Nation Energy Conservation Program, 37 Solar Hot Water Installations, 75 kW Solar Photovoltaic Installation CommuNITY INFoRmATIoN: Location: British Columbia, 36 km west of Victoria 2008 Population: 130 on reserve, 91 off reserve Area (hectares): 67.2 PRojECT INFoRmATIoN: Projected Cost: $1.3 Million (Includes 37 solar hot water installations, 75 kW solar photovoltaic installation and an ongoing energy conservation program): Energy Conservation Program: $100,000, Solar Hot Water Installation: $300,000, 75 kW Solar Photovoltaic Installation: $900,000 Power Capacity: 75 kW Photovoltaic Installation Projected GHG Reductions: 9 tonnes CO 2 annually (based on an average BC grid emission factor of 0.02 tonnes/MWh) Resource Savings: off-Grid: $9,400 annually on-Grid: $1,170 in savings annually, plus annual revenue of $4,219 by selling power to BC Hydro
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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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.027 | 0.022 |
| Scholarly communication | 0.012 | 0.011 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".