About Some Characteristics of Black English/à PROPOS DE CERTAINES CARACTÉRISTIQUES DE L'ANGLAIS DES NOIRS
Bibliographic record
Abstract
Paclitaxel is a promising drug in the treatment of different solid tumors. It exhibits nonlinear pharmacokinetics, particularly when administered as a constant rate infusion for shorter duration (e.g., 3 h). Because of the nonlinearity, relatively small changes in dose may lead to large changes in peak plasma concentration and total drug exposure. The study was conducted to evaluate the pharmacokinetics of different doses of paclitaxel administered intravenously as an infusion. A prospective study was conducted in 23 cancer patients aged between 28 and 74 years, treated with paclitaxel (130, 200, 230, and 260 mg/m(2)) over 3 h as constant rate infusion. Plasma samples were collected from all patients at 0, 1, and 3 h and for five patients at 5 and 13 h and paclitaxel concentrations were determined using high-performance liquid chromatography method. The overall mean clearance was found to be 47.5847 ± 142.028 l/h; the mean volume of distribution was 142.028 ± 73.438 l; mean elimination rate constant was 0.336 ± 0.002/h; mean half-life was 2.086 ± 0.009 h; mean area under the curve (AUC) was 5.5917 ± 2.707 mg/ml*h; and the mean of mean residence time was 2.980 ± 0.0131 h. Paclitaxel showed nonlinear kinetics and the pharmacokinetic parameters calculated were similar to those quoted in the literature. The peak plasma concentration at 130 mg dose level was 2 μ/ml, but an increase in dose was not associated with proportional increase in plasma concentration. No significant difference was found between pharmacokinetic parameters such as clearance, volume of distribution, and AUC at different dose levels.
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 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".