Application of broken-line analysis to assess floor space requirements of nursery and grower-finisher pigs expressed on an allometric basis
Bibliographic record
Abstract
Few issues in swine production are as complex as floor space allowances. One method for pork producers to calculate floor space allowance (A) is to convert BW into a 2-dimensional concept yielding an expression of A = k * BW0.667. Data on ADG, ADFI, and G:F were obtained from published peer-reviewed studies. Five data sets were created: A = grower-finisher pigs, fully slatted floors, and consistent group size; B = grower-finisher pigs and fully slatted floors (group size did not need to be consistent); C = grower-finisher pigs, partially slatted floors, and consistent group size; D = grower-finisher pigs, partially slatted floors (group size did not need to be consistent); and E = nursery pigs, fully slatted or woven wire floors (group size did not need to be consistent). Each data set was analyzed using a broken-line analysis and a linear regression. For the broken-line analyses, the critical k value, below which a decrease in ADG occurred, varied from 0.0317 to 0.0348. In all cases the effect of space allowance on ADG was significant (P <0.05). Using the linear analyses based on data with k values of 0.10); however, none of the linear regressions explained a significant proportion of the variation in ADG. The slopes for the nonplateau portion of the broken-line analyses based on percent values varied among data sets. For every 0.001 decrease in k (approximately 3% of the critical k value), ADG decreased by 0.56 to 1.41%, with an average value of 0.98% for the 5%-based analyses. The use of an allometric approach to express space allowance and broken-line analysis to establish space requirements seem to be useful tools for pig production. The critical k value at which crowding becomes detrimental to the growth of the pig is similar in full- and partial-slat systems and in nursery and grower-finisher stages. The critical point for crowding determined in these analyses approximated current recommendations to ensure the welfare of pigs.
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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 | 0.007 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".