Differentiated thyroid cancers: a comprehensive review of novel targeted therapies
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
Differentiated thyroid carcinoma (DTC) accounts for more than 90% of new thyroid cancer diagnoses, and includes papillary, follicular and Hürthle cell carcinoma. The prognosis for the vast majority of individuals diagnosed with DTC is excellent, with current treatment that includes surgery, radioactive iodine ablation and postoperative thyroid-stimulating hormone suppression. Unfortunately, the small proportion of individuals who develop radioactive iodine-resistant recurrent disease have few treatment options, and the vast majority will eventually die from their disease. Recently, several novel targets for anticancer agents have been identified and offer new hope for thyroid cancer patients diagnosed with progressive disease. In addition to targeting genes commonly altered in thyroid cancer, which include mutations in BRAF, RAS and RET, proangiogenic growth factor receptors and the sodium-iodide symporter have also been targeted. Several clinical trials evaluating tyrosine kinase and angiogenesis inhibitors for treatment of individuals diagnosed with metastatic or treatment-refractory DTC are currently underway. The objective of this review is to evaluate recent clinical trials that have studied novel targeted drugs for treatment of DTC.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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