A dynamic temperature model of mine water‐fed raceways used for microalgae biofuel production
Bibliographic record
Abstract
Abstract The mining industry is an extremely high consumer of energy, much of which is sourced from fossil fuels. The industry also generates outflows of “waste” energy in discharged gas, air, and water streams. Both the dependence on, and the environmental impacts of, fossil fuels could be reduced by on‐site energy recovery schemes that make use of both waste energy and the large tracts of the otherwise marginal or nonproductive land that mines sites create and occupy. One such possibility lies in the potential for on‐site use of the warm mine water from dewatering in raceways to support microalgae growth for biodiesel production. Mines are, however, often located in remote regions that can experience a significant range in seasonal ambient temperatures. In this article, a model that can be used to estimate the dynamic impact of a wide range of annual climatic conditions on the temperature of a specific volume of mine water flowing along a microalgae raceway is reported. © 2010 American Institute of Chemical Engineers Environ Prog, 2010
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".