THE INITIAL VALUE PROBLEM AROSE FROM UNPERTURBED HUMAN TUMOUR CELL LINES
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
To learn more of the phase distributions in unperturbed human tumour cells is a prerequisite prior to understanding of those in the perturbed cells. The work is important in understanding the efficiency of anti-cancer therapy. In this paper we investigate the existence, uniqueness and growth rate of the solution to a mathematical model of unperturbed human tumour cell line. At first, we construct the solution of this mathematical model by the method of continuation of solution, and then show the solution is unique. Finally, we find that the growth rate of the solution with respect to time is faster than exponential function. The basic mathematical techniques used here are variation of parameters and upper and lower solutions for differential equations. These results allowed one to estimate the cells population in each phase at specific time while one does not have cells mitosis DNA distribution data and it can also be used to compare with the perturbed cell lines.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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 it