Bibliographic record
Abstract
Gold Nanorod Photothermal Therapy (GNR-PTT) is a minimally invasive technique and an alternative to surgery for destroying tumors while sparing normal tissues. Gold Nanorods (GNRs) with strong extinction peaks in the near infra-red (NIR) spectrum is a good candidate to convert light into thermal energy to destroy tumors. Opto-acoustic imaging (OAI) is a non-invasive method that detects time-resolved acoustic waves created by short pulses of NIR in tissue. It leads to a pressure rise in the irradiated volume. The question of whether OAI is a suitable candidate for temperature monitoring of GNR-PTT in the NIR spectrum was examined. In this thesis, for the first time, GNRs in a gel phantom was used to monitor the temperature during PTT with different laser powers and GNR concentrations. The imaging was performed by a commercial device IMAGIO, Seno, TX. The results show changes of the OA signal follow to temperature changes. The concentration of GNR and the power have a significant role in producing good results.
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 | 0.000 | 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) | 0.001 | 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".