<i>IN-SILICO</i> PERFORMANCE INVESTIGATION OF NANOPARTICLE-ASSISTED PHOTO THERMAL ABLATION
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
In recent days, the number of cancer cases is escalating promptly around the world. In general, conventional ablation methods, encompassing comprehensive drawbacks, are employed to cure cancer. At present, photo thermal therapy (PTT) is showing great promise to the treatment of cancer. However, the effective implementation of this technology is utmost challenging as several parameters affect the tumor surroundings. In this work, the effects of different parameters on the performance of PTT have been thoroughly investigated by considering a realistic model of human tissue underneath the skin using a finite element solver, COMSOL Multiphysics. Two different conditions, with and without considering gold nanoparticles at tumor site, are investigated where a laser beam is used as a source of energy. Fluence rate, temperature distribution, and thermal damage are highlighted in this work. It is observed that by utilizing a miniature needle with integrated waveguide and gold nanoparticles, a tumor can be effectively eradicated along with assuaging the conventional drawbacks of PTT. This study would also be useful for designing operative PTT for different parts of human tissue.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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 it