Bibliographic record
Abstract
and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of these terms. The author reserves all other publication and other rights in association with the copyright in the thesis and, except as herein before provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission. in Purpose: evaluate 1) reliability and accuracy of cone-beam computed tomography (CBCT) for assessing adenoid size compared to nasoendoscopy (NE), 2) Influence of clinical experience on CBCT diagnosis. Methods: Four blinded evaluators reviewed randomized CBCT images. Adenoid size was graded on a 4-point scale for CBCT and NE (by an pediatric otolaryngologist). Reliability was assessed with intra and inter-observer agreement. Accuracy was assessed with agreement between CBCT and NE, plus sensitivity / specificity analysis. Results: 39 consecutively assessed, non-syndromic subjects (11.5 ± 2.8 years) were evaluated. CBCT demonstrated excellent sensitivity (88%) and specificity (93%), strong accuracy (ICC = 0.80, 95 % CI ± 0.15), and very good reliability, both within observers (ICC = 0.85, 95 % CI ± 0.08) and between observers (ICC = 0.84 ± 0.08). Clinical experience of the CBCT evaluators did not have a statistically significant effect. Conclusions: CBCT is a reliable and accurate tool for identifying adenoid hypertrophy.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.706 | 0.542 |
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".