18th Annual Scientific Meeting of the International Society for Biological Therapy of Cancer
Bibliographic record
Abstract
The 18th Annual Scientific Meeting of the International Society for Biological Therapy of Cancer (iSBTc) was held at the Hyatt Regency, Bethesda, MD, close to the National Institutes of Health (NIH) campus. The meeting was organised on behalf of the society by Neil Berinstein from Aventis Pasteur, Toronto, Canada, Janice P Dutcher from Our Lady of Mercy Medical Center, Bronx, NY and Francesco M Marincola from the NIH, Bethesda, MD. The 2003 meeting included 57 oral presentations and > 100 poster presentations. There were > 800 registrants to the Annual Meeting and the multiple satellite symposia. The iSBTc, formerly the Society of Biological Therapy (SBT), was founded by R Oldham in 1984. Its membership has been rapidly growing of late, with > 500 members at present. The purpose of the iSBTc is to bring together those diverse individuals actively investigating biologic agents and biological response modifiers in the treatment of cancer, including clinicians and basic scientists from industry, government and academia. The President of the Society is Dr Michael B Atkins from Beth Israel Deaconess Medical Center, Boston, MA and the Vice President is Ulrich Keilholz from UKBF, Free University Berlin, Germany.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.057 | 0.034 |
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".