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
INTRODUCTION: Specific delivery of a drug to a target site is a major goal of drug delivery research. Using temperature-sensitive liposomes (TSLs) is one way to achieve this; the liposome acts as a protective carrier, allowing increased drug to flow through the bloodstream by minimizing clearance and non-specific uptake. On reaching microvessels within a heated tumor, the drug is released and quickly penetrates. A major advance in the field is ThermoDox® (Celsion), demonstrating significant improvements to the drug release rates and drug uptake in heated tumors (∼ 41°C). Most recently, magnetic resonance-guided focused ultrasound (MRgFUS) has been combined with TSL drug delivery to provide localized chemotherapy with simultaneous quantification of drug release within the tumor. AREAS COVERED: In this article the field of hyperthermia-induced drug delivery is discussed, with an emphasis on the development of TSLs and their combination with hyperthermia (both mild and ablative) in cancer therapy. State-of-the-art image-guided heating technologies used with this combination strategy will also be presented, with examples of real-time monitoring of drug delivery and prediction of efficacy. EXPERT OPINION: The specific delivery of drugs by combining hyperthermia with TSLs is showing great promise in the clinic and its potential will be even greater as the use of image-guided focused ultrasound becomes more widespread - a technique capable of penetrating deep within the body to heat a specific area with improved control. In conjunction with this, it is anticipated that multifunctional TSLs will be a major topic of study in this field.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.026 |
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