Bibliographic record
Abstract
Water is our most valuable resource. It sustains life, environmental ecosystems and the economy. In Alberta, an integrated approach to water management is integral to our water conservation efforts. This means that a connection must be made in the use of water by municipalities, the agricultural sector and energy industry, while ensuring that the needs of the environment are met. The objective of this Capstone Project was to research, analyze, and provide policy recommendations on water management issues in Alberta. Specific emphasis was on understanding the role water valuation should play in water management for Alberta’s agricultural, energy and municipal sectors. Research was gathered through literature reviews and interviews with fourteen Alberta water experts. Recent implementations of the Land-Use Framework (2008) and the Water for Life strategy (2003) demonstrate the province’s pragmatic approach to land and water management. However, tangible tools and management strategies in Alberta are limited when connecting water for people, food, energy and the environment. Increased population growth and economic activity as well as impacts of climate change will strain Alberta’s water resources. In light of these pressures, a renewed approach to water management is required.
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 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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".