Nonlinear dose response relationships and inducible cellular defence mechanisms
Bibliographic record
Abstract
With the inclusion of inducible radioprotective mechanisms in a radiobiological state-vector model it was possible to explain plateaus in dose-response relationships for neoplastic transformation produced by in vitro irradiation of different cell lines with low-LET irradiation at high dose rates. The current study repeated the simulation of one data set that contains a plateau at mid doses. In contrast to earlier studies, the new one did not model the repair of double-strand breaks (DSBs) located in bulk DNA (likely via non-homologous end joining) as being inducible. Repair of specific DSBs located in actively transcribed genes was assumed to occur via homologous recombination and was considered to be inducible. This reduced the number of parameters that have to be determined by fitting the model to data. In addition, all types of radical scavengers were formerly considered to be inducible by radiation. This was redefined in the current work and the effectiveness of scavengers was implemented in a refined way. The current work investigated whether these and other model adjustments lead to an improved fit of the data set.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".