Bibliographic record
Abstract
The 2024 Geological Association of Canada -Mineralogical Association of Canada Meeting, held jointly with the 10 th International Symposium on Granitic Pegmatites, was hosted by Brandon University, Manitoba, between May 19 and 22, 2024.Under the banner of At The Heart Of The Continent, GAC-MAC-PEG 2024 offered a wide and diverse scientific program, with a strong critical minerals component, and several workshops and fieldtrips, as well as extensive outreach and Indigenous engagement programs.It also featured several social events and formal functions that contributed to bringing geoscientists together.The meeting was strongly supported by industry, academia, and government sponsors and hosted numerous exhibitors.This year's meeting was smaller than some previous GAC-MAC events, with 260 abstracts (190 oral and 70 poster presentations) and 350 attendees, perhaps due to the remoteness and perceived lack of appeal of Brandon.Nevertheless, the meeting attracted many international delegates from 25 coun-tries located on almost every continent -indeed, approximately a fifth of the delegates came from beyond Canada.Our diverse attendees were able to learn about the strong and successful Geology Department at Brandon University and about Brandon, the Wheat City, the largest equestrian centre in Canada, and home to a surprisingly successful hockey team, the Wheat Kings.Readers will be able to appreciate the breadth and diversity of the scientific program at the GAC-MAC-PEG 2024 meeting by perusing this issue of Geoscience Canada, which includes all the abstracts.Please note that some limited additional editing was applied as part of the publishing process, so for some there may be small differences from versions distributed at the meeting or available at the conference website.In most cases, these are just format-related matters, but there were a few cases where minor adjustments to grammar, spelling, and continuity of text were resolved to the best of the Geoscience Canada editors' abilities.A very small number of abstracts originally included references, funding acknowledgments or other material that is normally excluded from abstracts, and these were removed from the final layout.Readers who have specific questions about a given contribution or who are interested in clarification should contact the author(s).Registered users can access all abstracts on the conference website (event.fourwaves.com/gacmac2024/,under Presentations).On behalf of the GAC-MAC-PEG 2024 Local Organizing Committee, I thank all the contributors to its success, and hope that this published record will have long-term value in addition to interesting reading!
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.405 | 0.266 |
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".