Biological Markers of Boar Fertility
Why is this work in the frame?
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Full frame distilled prediction
Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
- Candidate categories
- none
- Consensus categories
- none
- Domain
- Candidate signal: noneConsensus signal: none
- Study design
- Candidate signal: Other designConsensus signal: none
- Genre
- Candidate signal: ReviewConsensus signal: Review
- Teacher disagreement score
- 0.980
- Threshold uncertainty score
- 0.908
- Validation status
machine_predicted_unvalidated·codex-gemma-dda1882f352a
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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)
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
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.
- Teacher spread
- 0.248 · how far apart the two teachers sit on this one work
- Validation status
score_only:v0-immature-baseline· verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it
Abstract
The semen evaluation techniques used in most commercial artificial insemination centers, which includes sperm motility and morphology measurements, provides a very conservative estimate of the relative fertility of individual boars. As well, differences in relative boar fertility are masked by the widespread use of pooled semen for commercial artificial insemination (AI) in many countries. Furthermore, the relatively high sperm numbers used in commercial AI practice usually compensate for reduced fertility, as can be seen in some boars when lower numbers of sperm are used for AI. The increased efficiency of pork production should involve enhanced use of boars with strong reproductive efficiency and the highest genetic merit for important production traits. Given that the current measures of semen quality are not always indicative of fertility and reproductive performance in boars, accurate and predictive genetic and protein markers are still needed. Recently, significant efforts have been made to identify reliable markers that allow for the identification and exclusion of sires with reduced reproductive efficiency. This paper reviews the current status of proteomic and genomic markers of fertility in boars in relation to other livestock species.
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.
The record
- Venue
- Reproduction in Domestic Animals
- Topic
- Sperm and Testicular Function
- Field
- Medicine
- Canadian institutions
- University of Alberta
- Funders
- not available
- Keywords
- FertilityArtificial inseminationBiologySemenSpermBOARInseminationSemen qualityBiotechnologyGeneticsDemographyPopulationPregnancy
- Has abstract in OpenAlex
- yes