Defining incidence and complications of fibrolamellar liver cancer through tiered computational analysis of clinical data
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
The incidence and biochemical consequences of rare tumor subtypes are often hard to study. Fibrolamellar liver cancer (FLC) is a rare malignancy affecting adolescents and young adults. To better characterize the incidence and biochemical consequences of this disease, we combined a comprehensive analysis of the electronic medical record and national payer data and found that FLC incidence is likely five to eight times higher than previous estimates. By employing unsupervised learning on clinical laboratory data from patients with hyperammonemia, we find that FLC-associated hyperammonemia mirrors metabolic dysregulation in urea cycle disorders. Our findings demonstrate that advanced computational analysis of rich clinical datasets can provide key clinical and biochemical insights into rare cancers.
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.
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 | 0.001 |
| 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