EFFECTS OF TERODILINE AND OXYBUTYNLNS ON CARDLAC MEMBRANE CURRENTS"
Bibliographic record
Abstract
licence allowing the National Libraiy of Canada to reproduce, loan, distri'bute or seii copies of this thesis m microfonn, papa or electronic formats. The author retains ownershrp of the copyright in this thesis. Neither the thesis nor substantial extracts fiom it may be printed or otheMrise reproduced without the author's permission. L'auteur a accordé une licence non exchive permettant a la Bibliothéqae nationale du Canada de reproduire, prêter, distriiuer ou vendre des copies de cette thèse sous la forme de microfichelfilm, de reproduction sur papier ou sur format électronique. L'auteur conserve la propriété du droit d'auteur qni protège cette thèse. Ni la thèse m des extmits substantiels de celle-ci ne doivent ê e imprimés ou autrement reproduits sans son autorisation DEDICATION This thesis is dedicated to my motber Dr. Pauline Alice Jones who passed away unexpectedly during the course of my thesis research. 1 want to thank her for the years of unconditional love, and al1 that she has done in my development and for making me aware of the tools that are required for living a full and rewarding life. TABLE OF CONTENTS
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.029 | 0.005 |
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".