An investigation of the associations between several candidate genes and reproductive traits in swine
Bibliographic record
Abstract
your insistence that we drink Canadian cocktails and hang around with the homeless at Minneapolis bus stops at 2AM? Thanks a lot for all the good times, you two.Thank you to my best friend over the past 8 years, Beth, for all her love and support during my time in grad school, and especially the past few months.Poor Beth has had to put up with my lovely moods over the past year as I tried to finish everything up.Beth, I owe you a great deal for putting up with me and reassuring me when I was not sure if it was worth it or not.I'm not quite sure what the next few years will bring, but just remember that the Frog, Brutus, and I will always love you.I've got to thank the two people who have been there for me through the past 29 years, and the past 10 years of school in particular, my parents.If it wouldn't have been for all the things you taught me as I was growing up, there is no way I could have made it through all these years of school.Thank you for listening to all my gripes for all these years and putting me on the right track.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. 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.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".