Tail-Biting in Pigs: A Scoping Review
Bibliographic record
Abstract
Tail-biting is globally recognized as a welfare concern for commercial swine production. Substantial research has been undertaken to identify risk factors and intervention methods to decrease and understand this vice. Tail-biting appears to be multifactorial and has proven difficult to predict and control. The primary objective of the scoping review was to identify and chart all available literature on the risk factors and interventions associated with tail-biting in pigs. A secondary objective was to identify gaps in the literature and identify the relevance for a systematic review. An online literature search of four databases, encompassing English, peer-reviewed and grey literature published from 1 January 1970 to 31 May 2019, was conducted. Relevance screening and charting of included articles were performed by two independent reviewers. A total of 465 citations were returned from the search strategy. Full-text screening was conducted on 118 articles, with 18 being excluded in the final stage. Interventions, possible risk factors, as well as successful and unsuccessful outcomes were important components of the scoping review. The risk factors and interventions pertaining to tail-biting were inconsistent, demonstrating the difficulty of inducing tail-biting in an experimental environment and the need for standardizing terms related to the 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 | 0.007 | 0.026 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.012 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".