PSIV-B-29 Evaluating the effect of different feeding strategies in feeding behavior through a novel behavior index integrating several components of the feeding behavior of finishing pigs
Bibliographic record
Abstract
Abstract Feeding behavior is an area of study that links the nutritional and behavioral sciences. However, describing the feeding behavior of pigs is difficult given the diversity of variables available and the large day-to-day intra-animal variation. The objectives of this study were to create an index integrating information from several components of feeding behavior that accounts for intra-animal variation, and to evaluate the capability of this index to study the impact of different feeding strategies in pigs’ feeding behavior. Feed intake information from 160 pigs during the last 28 days of the finishing phase from 3 datasets was used. For each pig, the sum of the absolute values of the deviation areas between the regression line of the relative cumulative feed intake and the observed cumulative feed intake was used to calculate the weekly index measuring the irregularity of feed intake (IIFI). Spearman’s correlations of IIFI with the number of daily meals (r = -0.42; P < 0.001), meal duration (r = 0.38; P < 0.01), and feed intake per meal (r = 0.41; P < 0.01) indicate that pigs with high IIFI have fewer meals of longer duration and higher feed intake compared to pigs with low IIFI. Analysis of variance in datasets 1 and 2 showed that moving from conventional to feeding precision systems does not interfere with the feeding behavior of finishing pigs (P > 0.05). In dataset 3, pig feeding behavior was more regular in control diets than for pigs fed fibrous diets (IIFI; 164 vs. 197, respectively; P < 0.05). Additionally, IIFI was smaller in pigs fed canola than in pigs fed wheat by-product diets. These results indicate that IIFI integrates information from several components of the feeding behavior of pigs and demonstrates its potential to evaluate the effect of feeding strategies on feeding behavior.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".