Bibliographic record
Abstract
CLINAM is a nonprofit organization based in Basel, Switzerland (www.clinam.org), that has been founded by Beat Löffler and Patrick Hunziker in 2007. The organization, utilizing its worldwide network of stakeholders, hosts an annual European and Global Summit for Clinical Nanomedicine in the fields of nanomedicine, targeted drug delivery, precision medicine, and other related fields. These summits relate to the main elements of cutting-edge medicine and the inclusion of the implications of nanomedicine for patients and mankind. In 2009, CLINAM founded the International Society for Nanomedicine (ISNM) with the participation of scientists and national organizations from Japan, Korea, the USA, Canada, Europe, South America, India, Australia, Africa, Australia, and India. ISNM is led by another member country every 2 years. Every 2 years, ISNM organizes a summer school, which brings together experienced researchers and students. Another important element of CLINAM is the European Society for Nanomedicine (www.esnam.org), which has more than 1000 members today.
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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 | 0.022 | 0.013 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.007 | 0.011 |
| Insufficient payload (model declined to judge) | 0.049 | 0.033 |
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".