Are Turkeys (Meleagris gallopavo) Motivated to Avoid Excreta-Soiled Substrate?
Bibliographic record
Abstract
The soiling of bedding on modern turkey farms combined with turkeys' reduced ability and opportunity to perch and roost at elevation, forces them to spend most, if not all, of their time in contact with their excreta. To determine turkeys' perspective on these conditions and the value they place on unsoiled bedding vs. soiled litter (collectively, substrates), we used twenty-four eleven-week-old turkey hens divided into six two-compartment pens. In the "home" compartment (H), we placed soiled wood shavings, while the "treatment" compartment (T) contained no substrate (NS), fresh pine and spruce wood shavings (FP), soiled pine and spruce wood shavings (SP), ammonia reductant-treated soiled pine and spruce wood shavings (TSP), or a feed treatment. One-way push-doors separated the two compartments. The door leading to T weighed an additional 0%, 20% or 40% of the turkeys' body weight while the door to H remained unweighted. All birds were exposed to each resource and door weight combination in a systematic order. We measured the turkeys' motivation based on the number of birds that pushed the maximum weight to access each resource, the amount of time spent in T, and the number of visits to T. Our findings show that turkeys worked harder to access feed compared to all the floor substrate treatments. Additionally, they were equally motivated to access all the substrate treatments.
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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 | 0.000 | 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) | 0.001 | 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".