Validation of Individual Computerized Sow Feeding Systems in Lactation
Bibliographic record
Abstract
Two experiments evaluated the accuracy of individual computerized feed delivery systems for lactating sows (GESTAL Solo, JYGA Technologies Inc., St-Lambert-de-Lauzon, Quebec, Canada). The feeders volumetrically dispense feed based on rotations of a screw auger. In Experiment 1, 29 prototype feeders were used across 3 farrowing groups. On d 0, 1 feeder was selected to calibrate the computer system to the bulk density of the lactation diet. Feeders were programmed for 5 feeding periods per day with feeding period allowing up to 4 feed drops triggered by the sow. Sows activate a trigger within the feed bowl to receive a targeted amount of feed (1.5 lb) and the computerized feeder records the delivery amount based on calibration values. In addition, total lactation feed intake was recorded by weighing the quantity of feed provided to the feeding system for each sow throughout lactation. Feed delivered by a single trigger activation on d 0, d 10, and d of weaning was collected and weighed with a scale and compared to the computer record. Additionally, total feed delivered over the lactation period was compared between the recorded computer measurement and scale weight. Average percentage difference between the two measurements ranged from 0.01 to 36.6% for a single trigger event. Computer-recorded total lactation feed intake was marginally less (P < 0.089) than the actual weight of feed delivered (230.3 vs. 239.9 lb; SEM 5.43). Individual feeders had recorded total feed delivery ranging from 77 to 122% of actual weight delivered. Based on these results, a new feeder design, identical to the commercially marketed GESTAL Solo (plastic hopper manufactured with injection mold instead of rotational mold), was tested in Experiment 2. In Experiment 2, 29 feeders were used in a single farrowing group to evaluate the new sow feeders. Feeders were calibrated and data were collected using the same procedures as Experiment 1, except individual feed drops were collected 8 times per feeder throughout lactation. Average percentage difference across all feeders ranged from 3.8 to 13.4%. There was no evidence (P < 0.542) of difference between the computer-recorded total lactation feed and actual weight of feed delivered (279.6 vs. 272.8 lb; SEM 4.03). Individual feeders had recorded total feed delivery ranging from 90.4 to 106.4% of actual weight delivered. Overall, this study shows the new feeder model was less variable in feed drops and total feed delivery than the old prototype.
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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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".