Advancing Medical Applications of Cancer Nanotechnology: Highlighting Two Decades of the <scp>NCI</scp>'S Nanotechnology Characterization Laboratory Service to the Research Community
Bibliographic record
Abstract
The Nanotechnology Characterization Laboratory (NCL) is a US federally funded resource providing characterization and expertise to the cancer nanomedicine research community. Founded as a formal partnership among the US National Cancer Institute (NCI), the US Food and Drug Administration (FDA), and the US National Institute of Standards and Technology (NIST), the NCL has spent two decades developing a one-of-a-kind service with broad multidisciplinary expertise to meet the needs of a rapidly evolving drug development field. To mark the 20th anniversary of the lab's founding, the NCL hosted a symposium to highlight the achievements of the cancer nanomedicine field, showcase novel, next-generation nanotechnology research, and discuss future priorities to enable continued growth in combating cancer and the complexities associated with treating a disease that continues to take millions of lives annually. The discussion topics from this event are summarized.
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How this classification was reachedexpand
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 | 0.008 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.002 | 0.008 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.005 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| 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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".