Estrategia de reaseguro proporcional óptima desde el punto de vista de la probabilidad de ruina: Un análisis con Mathematica 6
Bibliographic record
Abstract
Persons with hepatitis C virus (HCV) genotype 1a (GT1a) infections harboring a baseline Q80K polymorphism in nonstructural protein 3 (NS3) have a reduced virologic response to simeprevir in combination with pegylated interferon-alfa and ribavirin. We aimed to develop, validate, and freely disseminate an NS3 clinical sequencing assay to detect the Q80K polymorphism and potentially other HCV NS3 drug resistance mutations. HCV RNA was extracted from frozen plasma using a NucliSENS easyMAG automated nucleic acid extractor, amplified by nested reverse transcription-PCR, and sequenced using Sanger and/or next-generation (MiSeq) methods. Sanger chromatograms were analyzed using in-house software (RECall), and nucleotide mixtures were called automatically. MiSeq reads were iteratively mapped to the H77 reference genome, and consensus NS3 sequences were generated with nucleotides present at >20% called as mixtures. The accuracy, precision, and sensitivity for detecting the Q80K polymorphism were assessed in 70 samples previously sequenced by an external laboratory. A comparison of the sequences generated by the Sanger and MiSeq methods with those determined by an external lab revealed >98.5% nucleotide sequence concordance and zero discordant calls of the Q80K polymorphism. The results were both highly repeatable and reproducible (>99.7% nucleotide concordance and 100% Q80K concordance). The limits of detection (>2 and ∼5 log10 IU/ml for the Sanger and MiSeq assays, respectively) are sufficiently low to allow genotyping in nearly all chronically infected treatment-naive persons. No systematic bias in the under- or overamplification of minority variants was observed. Coinfection with other viruses (e.g., HIV and hepatitis B virus [HBV]) did not affect the assay results. The two independent HCV NS3 sequencing assays with the automated analysis procedures described here are useful tools to screen for the Q80K polymorphism and other HCV protease inhibitor drug resistance mutations.
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How this classification was reachedexpand
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 | 0.008 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".