SU‐FF‐T‐370: Properties of the Iso‐NTCP Envelope
Bibliographic record
Abstract
Purpose: To analytically investigate a property of the integral dose‐volume histogram (DVH) space. Method and Materials: A curve called an α‐iso‐NTCP envelope is constructed by connecting points belonging to step‐like integral DVHs each corresponding to partial organ homogeneous irradiation of relative volumes να to dose levels Dα such that the resulting NTCP is in all cases α %. The two subspaces into which the envelope divides the DVH space are analytically explored through comparing the values of the equivalent uniform doses (EUDs) corresponding to the different DVHs and using the fact that NTCP is a monotonic function of EUD as well as the monotonic nature of the integral DVH itself. Results: It is theoretically proven that any DVH passing through a point (Dα, να) from the α‐iso‐NTCP envelope, i.e. any DVH that crosses or is tangential to the envelope, will result in an NTCP⩾α%, the equality being valid only for the step‐like DVH corresponding to the partial organ homogeneous irradiation of να to Dα,. Thus, it is proven that any DVH that at least partially lies above the envelope result in NTCP>α%. For some of the DVHs lying under the envelope, e.g. those that are tangential to the envelope, it is also true that the resulting NTCP>α%. However, it was numerically demonstrated elsewhere that there exist DVHs lying entirely in the lower subspace that result in NTCP<α%. Conclusion: Since there is a chance that a DVH lying under the α‐iso‐NTCP envelope will result in NTCP<α%, it would therefore be preferable in the treatment optimization process to seek solutions for DVHs lying entirely under an iso‐NTCP envelope.
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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 | 0.005 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".