Support for catalysis in <scp>C</scp>anada by the <scp>CIC C</scp>atalysis <scp>D</scp>ivision and <scp>C</scp>anadian <scp>C</scp>atalysis <scp>F</scp>oundation
Bibliographic record
Abstract
Abstract 2020 and 2021 marked major milestones for the catalysis community in Canada. The Catalysis Division of The Chemical Institute of Canada marked its 50‐year anniversary in 2021, and the Canadian Catalysis Foundation celebrated its 30th anniversary in 2020. Both organizations have been instrumental in supporting and advancing the broad and evolving field of catalysis in Canada. This article summarizes the genesis of these organizations and highlights the key roles that they serve for the catalysis community. The health and vibrancy of the catalysis community in 2022 is a testament to the vision, insights, and efforts of those in the community in the 1960s and 1970s who created a framework that helped to bridge the gaps between science and engineering in the field of catalysis. The establishment of the Division in 1971 pulled together a critical mass of people with common professional interests in all aspects of catalysis and catalyst technology. The division structure facilitated collaborations, formalizing and organizing biennial catalysis symposia, administering award programs, and, now, acting as a pipeline for members and directors of the Canadian Catalysis Foundation.
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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.251 | 0.069 |
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".