Bibliographic record
Abstract
The 2nd International Conference on Drug Discovery and Therapy (ICDDT) was held from February 1–4, 2010 at Dubai Men's College, UAE. ICDDT 2010 was the second edition of this major international conference and exhibition, which aimed to present cutting edge advances in various disciplines on drug discovery and new therapeutics. The 2nd ICDDT proved to be a major pharmaceutical and medical research event of the UAE and was covered by the print and electronic media of the region. The conference hosted over 700 pharmaceutical scientists and clinical researchers who discussed the latest global breakthroughs in drug discovery and therapeutic research. Leading industrial and academic experts from 74 countries around the globe presented their findings in the form of Plenary Lectures, Invited Lectures, Session Lectures and Posters at this four–day conference. The conference agenda included more than 300 talks and 250 poster presentations in 23 conference tracks. There was a parallel commercial exhibition where both local and international companies exhibited their products. The 2nd edition of ICDDT provided a platform for all pharmaceutical scientists, internists and primary care physicians to discuss and learn about all the important international breakthrough developments on drug discovery and new therapeutics. The conference witnessed global participation from academia and industry. 731 delegates from 75 countries attended the conference. Majority of the participants were from USA, UK, Germany, Canada, Spain, Japan, Italy, Australia, South Korea, India and UAE.
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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.077 | 0.053 |
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".