Dedicated To My Family Especially My Sister Letty ACKNOWLEDGMENTS
Bibliographic record
Abstract
I greatly appreciated the opportunity to increase my knowledge and interests in research at the academic level specifically in the field of biotechnology. I am indebted to Agriculture and Agri-Food Canada for providing financial support to pursue this degree. Special thanks to my advisor Dr. Atkinson for allowing me to join the exciting group of Vitamin E research and for keeping his door open to provide continued guidance, encouragement, support and expertise. I wish to express my gratitude to Candace for her fiiendship, helpful suggestions and constructive criticisms throughout this project. Thanks to all the wonderfiil people at the laboratory of the Cool Climate Oenology and Viticulture Institute at Brock University. Finally, many thanks to the most important people in my life... my mom, dad, brothers and sisters; you have instilled in me a desire to continue my pursuit for knowledge, which is the
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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 | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.004 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.013 |
| Insufficient payload (model declined to judge) | 0.035 | 0.034 |
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".