Bibliographic record
Abstract
We present a brief overview of Canadian meteorites with a focus on noting significant recent falls, finds, and research developments. To date, 60 Canadian meteorites have received official international recognition from the Nomenclature Committee of the Meteoritical Society, while at least 13 more are “in process” for submission to the Meteoritical Bulletin, that organization’s official database of the world’s meteorites. The 60 meteorites (44 finds and 16 falls since the recognition of the Madoc iron in 1854) include 25 irons, 3 pallasite stony-irons, and 32 stony meteorites. The latter include 14, 11 and 3 H, L and LL chondrites, 2 carbonaceous chondrites and 2 enstatite chondrites, but no achondrites. The most intensively researched meteorites are Tagish Lake (C2 ungrouped) and Abee (EH5), followed by Bruderheim (L6) and Springwater (pallasite). Bruderheim, a 1960 fall, is widely distributed, being the most massive reported Canadian meteorite at 303 kg total known weight (TKW). Seven Canadian meteorites exceed 100 kg TKW, 36 are between 1 and 50 kg, and 17 are <1 kg. Recent years have seen the addition of the Tagish Lake, Buzzard Coulee and Grimsby meteorite falls, all of which have well-determined fireball trajectories and therefore well-known orbits, a striking Canadian addition to the handful that are known worldwide. The discovery of the Holocene Whitecourt iron impact crater is similarly a significant recent development in understanding the impactor flux. The lessons learned on meteorites can be applied to newly recovered samples from the Moon, Mars, asteroids, and comets.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.013 | 0.017 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 0.004 |
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".