188: Volumetric Whole Brain Irradiation Evaluation
Bibliographic record
Abstract
analysis.Patients were categorized into three groups based on their cavity visibility on CT: C1 (indistinct or no visible cavity); C2 (moderately visible cavity with indistinct borders); and C3 (highly visible cavity).Three observers manually registered the CBCTs for each patient utilizing two methods and materials: matching the ipsilateral breast/chest wall and lung interface as the target surrogate, and direct registration to the cavity.Krippendorff's alpha was used to assess agreement between the two methods.Root mean square (RMS) was calculated to assess the difference between observers.Results: Thirty breast boost patients, 10 in each cavity visualization category, were included for analysis.A total of 150 CBCT images were analyzed by each observer.Registration to the ipsilateral chestwall/breast reported a median RMS error of 0.1989 between observers.Direct registration to the cavity resulted in a median RMS error of 0.1784 between observers.The Krippendorff's alpha for ipsilateral chestwall/breast registration in C1, C2 and C3 patients in the left-right (LR), cranio-caudal (CC), and anterior-posterior (AP) directions were: 0.8,0.84,0.9; 0.81, 0.72, 0.55; and 0.78, 0.6, 0.52, respectively.The Krippendorff's alpha for direct cavity registration in C1, C2 and C3 patients in the LR, CC, and AP directions were: 0.72, 0.64, 0.84; 0.86, 0.72, 0.62; and 0.75, 0.6, 0.58, respectively.The ranksum difference between registration methods was p = 0.1538, with variation reported between cavity visualization categories (C1, p = 0.8903, C2, p = 0.0257, C3, p = 0.9450).Conclusions: Image registration to the ipsilateral breast/chest wall and lung interface for breast boost RT was more consistent than direct registration to the cavity, resulting in lower interobserver variability for breast boost IGRT.Varying visibility of the post-operative tumour bed on CBCT images limits direct registration to the breast cavity.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".