Geological Association of Canada-Newfoundland and Labrador Section Abstracts: Spring Technical Meeting, February 22 and 23, 2021
Bibliographic record
Abstract
The Annual Technical Meeting was held virtually on February 22 and 23, 2021 from various home offices, dens, and bedrooms across St. John’s, Newfoundland and Labrador and beyond.This year the meeting kicked off on Monday with a Special Session to pay tribute to R. Frank Blackwood who passed away in the summer of 2020. Frank was a strong supporter of bedrock mapping, mineral exploration, and the mining industry in Newfoundland and Labrador which is reflected in the following abstracts. Tuesday featured a General Session with presentations on a wide range of geoscience topics.As always, this meeting was brought to participants by volunteer efforts and would not have been possible without the time and energy of the executive and other members of the section such as Anne Westhues, Jared Butler, James Conliffe, Shawn Duquet, Sarah Hashmi, Zsuzsanna Magyarosi, Annie Parrell, and Karen Waterman. The organizers are also indebted to their sponsors, particularly the Geological Association of Canada, Department of Earth Sciences (Memorial University of Newfoundland), and the Geological Survey of Newfoundland and Labrador, Department of Energy, Industry, and Technology.Although the abstracts are modified and edited as necessary for clarity and to conform to Atlantic Geology format and standards, the journal editors do not take responsibility for their content or quality.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.164 | 0.097 |
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".