Bibliographic record
Abstract
Abstract The thyroid gland is composed of follicular cells, parafollicular cells, and connective tissue with occasional lymphocytes. Each of these cell types can give rise to histologically distinct tumors that differ significantly in behavior, prognosis, and response to treatment. The commonest tumors by far are those derived from follicular epithelial cells; these tumors are classified as differentiated (papillary and follicular), poorly differentiated (insular), and undifferentiated (anaplastic). Medullary thyroid cancers are derived from parafollicular cells. Tumors derived from lymphocytes and connective tissue cells are similar to such lesions elsewhere in the body, but a detailed discussion of those entities is beyond the scope of this chapter. In one of the earliest studies on prognostic factors in thyroid cancer, the multivariate analysis of the European Organization for Research and Treatment of Cancer (EORTC) Thyroid Cancer Co‐operative Group, all histologies were combined. The 5‐year survival ranged from 80% in differentiated carcinoma (papillary and follicular), to 55% in medullary thyroid carcinoma (MTC), to 10% in anaplastic carcinoma. Most subsequent studies of prognostic factors in thyroid cancer were developed for individual histologic types [differentiated papillary–follicular, poorly differentiated (insular), medullary, and anaplastic thyroid carcinomas] and they will be considered separately in this review. Some studies combine papillary and follicular, while others do not. The focus of this chapter is a review of the tumor‐, host‐ and environment‐related prognostic factors in differentiated thyroid cancer, with an additional discussion of prognostic factors in other thyroid histologies.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.143 | 0.099 |
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".