Location of Nursery Pigs in Relation to a Human Observer
Bibliographic record
Abstract
The objective of this experiment was to determine pigs’ location in their home pen in relation to an unknown female observer. A total of 79 pens housing 1,817 ~6 wk old mixed sexed nursery pigs were used. An approachability test defined by Fangman et al. (2010) was used. The length of the nursery pen was measured with the Adobe Photoshop ruler tool from the pen gate located directly behind the midpoint of the observer’s back (defined as the dorsal medial point) to the opposite end of the pen 20 cm from the floor. A transparency was taped to the computer monitor and the home pen was divided into thirds and fourths. Pigs were then counted within the lines. A pig was considered in a section if both eyes and at least one complete ear were in front of the line. These results will be presented descriptively. Fewer pigs were in the section closest to the observer (6.4% vs. 2.7 %; Figure 1) when the pen was divided into fourths. Pigs included in these closest sections to the observer were most likely to be classified as approaching. Regardless of how pens were divided up, more pigs were located in the furthest section away from the human observer (52.9 and 41.8% respectively; Figure 2). The observer noted portioning the pen into fourths provided greater pig location accuracy. For example when the pen was sectoioned into thirds, a toal of 15 pigs could not be clearly alloacted to a section compared to only four pigs when the pen was divided into fourths. In conclusion dividing the pen into fewer sections resulted in a higher percentage of pigs being classified as approaching the observer, however the accuracy of being able to place pigs into sections was harder when the pen was divided into thirds.
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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 | 0.002 | 0.004 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".