Oil Sands Monitoring (OSM) Program : science and monitoring strategic plan
Bibliographic record
Abstract
The Oil Sands Monitoring (OSM) Program is co-managed by the governments of Canada and Alberta, together with Indigenous communities and industry. The Program seeks to enhance understanding of the effects of oil sands development activities through ambient environmental monitoring in the oil sands region. The development of the first Science and Monitoring Plan 2024-29 (the Strategic Plan) is an important milestone for the Program. The Stratgeic Plan was developed and approved through consensus within the Oversight Committee of the OSM Program, representing Indigenous communities, industry and government. The four broad program strategic priorities include: Moving to an integrated, risk-based adaptive monitoring and evaluation program that reflects diverse knowledge systems and informs decision making, Ensuring that OSM Program data and information is accurate, timely, relevant and accessible, Improving program reporting, knowledge synthesis and communication to OSM members, decision-makers and the public, and; Enhancing program governance effectiveness and efficiency for program delivery and reinforcing a strong multi-stakeholder planning and decision-making process. The Strategic Plan will provide high-level direction and program expectations for the development and implementation of the annual Ambient Monitoring Work Plan, which includes monitoring of air, water, wetlands, biodiversity and Indigenous Community-based Monitoring.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.017 | 0.007 |
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".