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
BACKGROUND: Neuroendocrine/Merkel cell carcinoma (MCC) of the skin is an uncommon tumour. Currently, there are only limited data available on the natural history, prognostic factors, and patient management of MCC. OBJECTIVES: To review our experience and build the largest database from the literature. METHODS: Twenty-eight cases from the London Regional Cancer Center were combined with 633 cases obtained from the literature searched in English, French, German, and Chinese for the years 1966 to 1998. The database included age, sex, initial disease status at presentation to the clinic, site of primary, any coexisting disease, any previous irradiation, sizes of primary/nodal/distant metastases, management details, and final disease status. A new modified staging system was used: stage Ia (primary disease only, size > 2 cm), stage Ib (primary disease only, size > 2 cm); stage II (regional nodal disease), and stage III (beyond regional nodes and/or distant disease). RESULTS: Age > 65 years, male sex, size of primary > 2 cm, truncal site, nodal/distant disease at presentation, and duration of disease before presentation (< or =3 months) were poor prognostic factors. Surgery was the initial treatment of choice and it significantly improved overall survival (p =.004). CONCLUSIONS: We identified poor prognostic factors that may necessitate more aggressive treatment. The suggested staging system, incorporating primary tumour size, accurately predicted outcomes.
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) | 0.003 | 0.001 |
| 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 | 0.001 |
| 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