The Meteoritical Bulletin, No. 106
Bibliographic record
Abstract
Abstract Meteoritical Bulletin 106 contains 1868 meteorites including 10 falls (Aiquile, Broek in Waterland, Degtevo, Dingle Dell, Dishchii'bikoh, Hradec Králové, Kheneg Ljouâd, Oudiyat Sbaa, Serra Pelada, Tres Irmaos), with 1386 ordinary chondrites, 166 carbonaceous chondrites, 119 HED achondrites, 48 Lunar meteorites, 37 iron meteorites, 36 ureilites, 19 Martian meteorites, 13 enstatite chondrites, 12 Rumuruti chondrites, 9 primitive achondrites, 8 mesosiderites, 5 enstatite achondrites, 4 ungrouped achondrites, 4 pallasites, and 1 relict meteorite. A total of 958 meteorites are from Africa, 405 from Antarctica, 245 from Asia, 228 from South America, 12 from North America, 8 from Europe, 5 from Mars, 4 from Oceania, and 1 from an unknown location.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.118 | 0.101 |
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".