Bibliographic record
Abstract
Potential conflict of interest: Dr. Bruix consults for, advises for, is on the speakers' bureau for, and received grants from Bayer. He consults for, advises for, and is on the speakers' bureau for BTG. He consults for and advises for Novartis and Roche. He consults for and received grants from Daichi and Arqule. He consults for Abbott, Bristol‐Myers Squibb, GlaxoSmithKline, Lilly, and Kowa. He received grants from Sirtex. Dr. Sapisochin receives research support from Bayer. We appreciate the interest of Dr. Gu in our study. As mentioned in their letter, we agree that there are selected patients in which liver transplantation (LT) for intrahepatic cholangiocarcinoma (iCCA) may represent an excellent treatment option achieving good long‐term outcomes.1 In our cohort, ∼30% of the patients had hepatitis B virus infection and <20% were patients with primary sclerosing cholangitis, so we believe our study did not only represent Western countries. On the other hand, the numbers in our study did not allow performing accurate subgroup analysis according to underlying liver disease. We are therefore unable to comment on potential better outcomes of patients with HBV and if the results of LT in these patients are better to other indications is unknown. As mentioned in their letter, we agree that a major risk factor is viral hepatitis infection and cirrhosis and therefore these patients will benefit from surveillance programs.3 Even though these patients most likely will not have a high Model for End‐Stage Liver Disease score, they would need to be granted with exception points (as was done with hilar cholangiocarcinoma).4 The role of antiviral therapy for HBV and its outcomes post‐LT could not be evaluated in our cohort. Nevertheless, we believe that the impact of this therapy on post‐LT outcomes for iCCA should be similar to those in HBV patients transplanted for HCC. Finally, even though neoadjuvant chemoradiation has been shown to be safe and effective under a strict protocol for patients with hila cholangiocarcinoma pre‐LT5 and given that the results of LT for “very early” iCCA show a 5‐year survival ∼65% without neoadjuvant therapy, we are uncertain at this point if this will need to be implemented. It is possible though that this will be considered as a strategy for patients with larger iCCA under a research protocol.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.021 | 0.022 |
| Insufficient payload (model declined to judge) | 0.049 | 0.033 |
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".