Proceedings of the 63rd Conference of Metallurgists, COM 2024
Bibliographic record
Abstract
COM 2024, the 63rd Annual Conference of Metallurgists, was a remarkable event organized by the Metallurgy and Materials Society (MetSoc) of the Canadian Institute of Mining, Metallurgy and Petroleum (CIM).It brought together an impressive array of activities, including nine symposia, three plenary talks, 26 keynote presentations, and approximately 350 oral and 50 poster presentations.Additionally, the conference featured two panel discussions and a "Big Ideas" forum, providing a platform for participants to share novel and far-reaching ideas with a broad audience, potentially attracting interest in and facilitating the realization of their projects.This volume brings together the research papers and extended abstracts presented at COM 2024.The reader will appreciate the diverse range of topics covered in these publicationsfrom developing areas like advanced manufacturing, critical materials, and "greening" our industry, to long-standing subjects such as biohydrometallurgy, electrometallurgy, the development of light metal alloys, and dealing with arsenic and corrosion.This has been a true reflection of the COM 2024 theme: "Clean Technologies for a Materials-Intensive Future."The quality of these publications shows the collective effort of authors, symposium organizers, and peer reviewers, who worked hard to meet rigorous standards and tight deadlines.MetSoc upholds the principle that those who wish to present should also publish, ensuring the dissemination of high-quality research.MetSoc's recent partnership with Springer has been a significant step forward, ensuring that papers presented at COM receive welldeserved recognition and credit within the global publishing landscape.As a special note, I would like to personally thank the show management and the symposium Chairs and Co-chairs of COM 2024 listed in the following pages, who provided enormous time as volunteers to ensure the excellent quality of the programming.Finally, I would like to thank my employer, Rio Tinto Iron & Titanium, for supporting my leadership role in this event for the public benefit.In summary, I see these proceedings as a useful reference to the continually challenging world of metallurgy, materials, and sustainability.Further, I hope that the success of COM 2024 will be replicated in future COMs, benefiting the Canadian and international metallurgical and materials communities and ensuring the longevity of MetSoc itself.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".