Pesquisa de células malignas circulantes em pacientes com melanoma maligno de coróide
Bibliographic record
Abstract
PURPOSE: The purpose of our study was to detect circulating malignant cells (CMCs) in oversea-shipped blood samples of patients with uveal melanoma diagnosed in Brazil. METHODOS: Melan-A and tyrosinase were the two markers used for the detection of CMCs, using reverse transcriptase nested polymerase chain reaction (RT-nested-PCR) in 6 patients with uveal melanoma. The expression of beta-actin and GAPDH were used to assess the quality of the material. RESULTS: Five patients (83.33%) tested positive for the presence of CMCs. The RT-nested-PCR was positive for melan-A in 4 patients (66.7%) and positive for tyrosinase in 4 (66.7%) of the 6 patients. Three (50%) patients were positive for both markers. One (16.7%) patient was negative for both markers. All negative controls were negative. CONCLUSION: The quality of the blood samples shipped overseas, from patients with uveal melanoma, was preserved. The detection of CMCs using RT-nested-PCR was positive in the majority of the patients.
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.
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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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 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".