IDS2018. 21st International Drying Symposium. Proceedings
Bibliographic record
Abstract
The institutional organizers of IDS 2018 are the Department of Food Technology at the Universitat Politècnica de València and the Department of Chemistry at the University of Illes Balears. Like its previous biannual IDS conferences, the objective of 21th IDS is to provide the most advanced and comprehensive global forum for disseminating results and data in research, development, and applications in drying/dewatering sciences and technologies.This Symposium will be held in the main campus of the Universitat Politècnica de València and aims to bring together leading researchers and engineers from academia and from industry from all around the world in this university environment. It is also planned during the meeting an exposition of industrial equipment and developments. An Award program will be also part of the event for the international drying community. This Symposium is the 21th event in the series founded by Professor Arun S. Mujumdar at McGill University, Montreal, Canada, in 1978
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.170 | 0.104 |
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".