Lung cancer biopsies: Comparison between simple 22G, 22G upgraded and 21G needle for EBUS-TBNA
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Introduction: Novel technologies are currently used for lung cancer diagnosis. EBUS-TBNA 22G is considered one of the most important tools. However; there are still issues with the sample size. Patients and Methods: 223 patients underwent EBUS-TBNA with a 21G Olympus needle, 22GUS Mediglobe and 22GUB Mediglobe. In order to evaluate the efficiency of 22GUB novel needle design. In order to evaluate the sample size of each needle, we constructed cell blocks and measured the different number of slices from each biopsy site. Results: The 22GUB novel needle had similar and larger number of slices from each biopsy site compared to 21G needle. Discussion: Firstly as a novel methodology we used the number of slices from the constructed cell blocks in order to evaluate the sample size. Secondly, we should seek novel needle designs and not only concentrate on the volume of the sample size.
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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) | 0.001 | 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 it