The Meteoritical Bulletin, No. 103
Bibliographic record
Abstract
Abstract Meteoritical Bulletin 103 contains 2582 meteorites including 10 falls (Ardón, Demsa, Jinju, Križevci, Kuresoi, Novato, Tinajdad, Tirhert, Vicência, Wolcott), with 2174 ordinary chondrites, 130 HED achondrites, 113 carbonaceous chondrites, 41 ureilites, 27 lunar meteorites, 24 enstatite chondrites, 21 iron meteorites, 15 primitive achondrites, 11 mesosiderites, 10 Martian meteorites, 6 Rumuruti chondrites, 5 ungrouped achondrites, 2 enstatite achondrites, 1 relict meteorite, 1 pallasite, and 1 angrite, and with 1511 from Antarctica, 588 from Africa, 361 from Asia, 86 from South America, 28 from North America, and 6 from Europe. Note: 1 meteorite from Russia was counted as European. The complete contents of this bulletin (244 pages) are available on line. Information about approved meteorites can be obtained from the Meteoritical Bulletin Database (MBD) available on line at http://www.lpi.usra.edu/meteor/ .
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.202 | 0.210 |
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".