Systematic review of the effect of perch height on keel bone fractures, deformation and injuries, bone strength, foot lesions and perching behavior
Bibliographic record
Abstract
This report provides a summary of four systematic reviews on the impact of perch height on laying hen keel bone fractures, deformation and injuries, bone strength, foot lesions and perching behavior. After conducting a scoping review and identifying outcomes of interest, the review protocols were developed. An extensive literature search was conducted in information sources such as CABI, PUBMED and relevant conference proceedings. 1518 abstracts were assessed for relevance and 9 studies reported perch use and 1 reported keel injuries. No studies reported summary effect sizes; therefore it was not possible to conduct a meta-analysis. In lieu of a formal meta-analysis, a descriptive analysis was conducted, which plotted reported perch height against metrics of perch use. This descriptive analysis was not able to account for lack of independence, differences in sample size and other importance sources of heterogeneity such as cage height. The descriptive analysis suggested a positive association with metrics that measured perch use and height, i.e., increased usage was associated with increased height.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.011 | 0.053 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.011 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".