Клинико-эпидемиологические аспекты заболеваний шейки матки, ассоциированных с вирусами папиллом
Bibliographic record
Abstract
The study of clinical and epidemiological aspects of uterus cervix diseases associated with HPV has been performed. Materials and methods: 50 healthy women and 226 patients with uterus cervix diseases were included into prospective investigation. The diagnostics of HPV types was held with PCR test-systems AmplySens-100-R (Moscow). HPV is widely spread. The patients with HPV and CIN were younger than those with tumors. The development of tumors was associated with HPV. 18 th type of HPV was predominant in cervical squamous cell tumors, 16 th HPV type prevailed in CIN III, intraepithelial and micro invasive cancer, 18 th and 33 rd types in cervical invasive carcinomas. Diagnostics of HPV types is necessary for defining group of risk and preventive examination for uterus cervix cancer.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.019 | 0.007 |
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".