Impact of biofuel production on water demand in Alberta.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The production of biofuels (e.g., ethanol and biodiesel) requires a significant amount of water during feedstock production, transportation, and its conversion into biofuels. Therefore present study devoted to study the impact of biofuel production on water demand in Alberta. In scenario #1, it is assumed that ethanol is produced from both wheat and wheat straw and that biodiesel is produced from rapeseed. Scenario #2 proposes ethanol production from wheat only and biodiesel production from rapeseed. The water requirements for biofuel production in both scenarios are calculated for Alberta for the year 2025. Data on the current availability of water in Alberta indicate that the Athabasca, North Saskatchewan, and Peace River basins of northern Alberta have enough water to grow crops for the production of biofuels. In 2025, Alberta will have to produce 3,754 million liters of ethanol and 270 million liters of biodiesel to meet the projected levels. If biofuels are produced from the crops grown in the above-mentioned northern river basins, the province of Alberta should be able to meet biofuel demand in 2025 sustainably. The water requirement from these river basins for biofuel production will increase to 5.2%, 0.6%, and 11.6%, respectively, of the natural flow in scenario #1 whereas, for scenario #2, the water requirement from these rivers basins will increase to 5.2%, 2.3%, and 16.1%, respectively, of natural flow. These increases in the requirements are much lower than the possible allowed withdrawal levels.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it