Bibliographic record
Abstract
We thank Drs. Caturelli and Ghittoni for drawing attention to our study. We are, however, unsure if due diligence was given to the review and interpretation of our article. Caturelli and Ghittoni contend that the incidence of hepatocellular carcinoma (HCC) among indeterminate nodules in our study is too low. As mentioned in the Discussion section, our reported incidence of 13%-24% is well within the range of 9%-33% reported by three European studies.1 The reason for the low incidence is the more sensitive imaging diagnostic criteria for 1-2 cm HCC in the updated American Association for the Study of Liver (AASLD) guidelines, where now one of two, rather than both, positive contrast imaging scan is required for diagnosis of malignancy.2 Furthermore, their suggestion that a smaller criterion for nodule growth than our 30% increase in diameter be used is highly unrealistic, given inter- and intraobserver variability for measuring 1-2 cm nodules. Precisely for this reason were the Response Evaluation Criteria In Solid Tumors (RECIST) criteria revised to the current 1.1 version. A criterion of a minimum of 5 mm growth in the single largest diameter of target lesion was added to avoid interpreting measurement error in small lesions as progressive disease.3 Caturelli and Ghittoni indicate puzzlement as to why some of our nodules were not visible on grayscale ultrasound. We have described in our methodology the realistic inclusion of nodules that were found on subsequent computed tomography (CT)/magnetic resonance imaging (MRI) work-up imaging. Additionally, the authors misinterpreted the aim of our study, which was to identify variables with significant association with HCC that would allow selective application of biopsy to a subset of indeterminate 1-2 cm nodules. Our aim was not to measure the impact of biopsy. Finally, biopsy sampling error is expected for such small nodules and that is why the AASLD guidelines ignore negative biopsies and recommend close follow-up or rebiopsy.2 Forner et al.4 reported 30% and 39% false-negative biopsy rates for first and second biopsies of HCCs. We want to vigorously stress that the aim of oncology is not the successful treatment of tumors, as Caturelli and Ghittoni suggest, but rather increasing patient survival. The treatment of “very early HCCs” has not been studied in such a way. When the majority of indeterminate nodules remain stable in the long-term, it is reasonable to limit biopsy and treatment to those who are predisposed to growth while closely following the others. Korosh Khalili M.D.*, Morris Sherman M.D. , * Department of Medical Imaging, University of Toronto, University Health Network, Princess Margaret Hospital, Toronto, ON, Canada, Department of Gastroenterology, University of Toronto, University Health Network, Princess Margaret Hospital, Toronto, ON, Canada.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.696 | 0.489 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".