Extraction & Processing Division: Activities and Updates
Bibliographic record
Abstract
Extraction & Processing Division Sponsored Symposia Symposium Organizers 3rd International Symposium on High Temperature Metallurgical Processing Jiann-Yang Hwang, Tao Jiang, Patrick Masset, Onuralp Yucel, Rafael Padilla, Guifeng Zhou Battery Recycling Gregory K. Krumdick, Linda Gaines CFD Modeling and Simulation in Materials Processing Laurentiu Nastac, Lifeng Zhang, Brian G. Thomas, Adrian Sabau, Nagy ElKaddah, Adam C. Powell, Herve Combeau Characterization of Minerals, Metals, and Materials Jiann-Yang Hwang, Sergio Montero, Chenguang Bai, John Carpenter, Donato Firrao, Byoung-Gon Kim, Mingdong Cai Electrometallurgy 2012 Michael L. Free, Georges Houlachi, Antoine Allanore, Michael Moats, Edouard Asselin, Shijie Wang, James Yurko Energy Technologies and Carbon Dioxide Management Maria Salazar-Villalpando, Neale R. Neelameggham, Donna P. Guillen, Subodh Das, Ramana Reddy, Animesh Jha, Soobhankar Pati, Mark Jolly, Lakshmanan Vaikuntam International Smelting Technology Symposium (Incorporating the 6th Advances in Sulfide Smelting Symposium) Jerome P. Downey, Thomas P. Battle, Jesse White
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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; a candidate call from one teacher head, 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".