Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Meteoritical Bulletin 104 contains 2279 meteorites including 12 falls (Annama, Cartersville, Creston, Diepenveen, Famenin, Izarzar, Nkayi, Porangaba, San Juan de Ocotán, Trâpeăng Rônoăs, Xinglongquan, Žd’ár nad Sázavou), with 1847 ordinary chondrites, 138 carbonaceous chondrites, 128 HED achondrites, 38 lunar meteorites, 24 ureilites, 22 Martian meteorites, 19 iron meteorites, 17 primitive achondrites, 14 enstatite chondrites, 10 mesosiderites, 9 Rumuruti chondrites, 5 pallasites, 4 ungrouped achondrites, 2 enstatite achondrites, 1 ungrouped chondrite, and 1 Kakangari chondrite, and with 996 from Antarctica, 790 from Africa, 337 from Asia, 111 from South America, 30 from North America, 11 from Oceania, and 4 from Europe. Note: 1 meteorite from Russia was counted as European.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it