Evaluation of water usage and water conservation strategies in the swine industry
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
Water is a critical input in swine operations but often neglected because of the prevailing notion that water will always be available in unlimited quantity. However, excessive use of water can have negative impact on the environment and cause depletion of water resources. In swine operations, water is used for animal drinking, cooling, cleaning, and domestic consumption. The rate of water use from different stages of swine production has impact on the overall production cost. Poor production practices may lead to higher water consumption and increased manure slurry volume which needs further handling and treatment, representing added cost. The objectives of this study are to assess the water usage in different stages of pig production and to compile the available water conservation management practices. The applicability of these conservation measures in swine production operations in terms of technical viability, economic costs for implementation, and benefits to the overall operation will be assessed. Preliminary results from this work included calculation of the current rate of water usage to produce each pig based on the literature review and survey of swine producers in Saskatchewan. Furthermore, the different technologically-feasible water conservation practices that pork producers can implement in their operations to reduce their water usage were ranked.
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 | 0.001 | 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