A comment on “An evolutionary system of mineralogy: Proposal for a classification of planetary materials based on natural kind clustering”
Bibliographic record
Abstract
Abstract The classification and nomenclature of mineral species is regulated by the Commission on New Minerals, Nomenclature and Classification of the International Mineralogical Association (IMACNMNC). This mineral species classification is necessary for Earth Sciences, as minerals constitute most planetary and interstellar materials. Hazen (2019) has proposed a classification of minerals and other Earth and planetary materials according to “natural clustering.” Although this classification is complementary to the IMA-CNMNC mineral classification and is described as such, there are some unjustified criticisms and factual errors in the comparison of the two schemes. It is the intent of the present comment to (1) clarify the use of classification schemes for Earth and planetary materials, and (2) counter erroneous criticisms or statements about the current IMA-CNMNC system of approving proposals for new mineral species and classifications.
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 | 0.014 | 0.057 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.009 | 0.013 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.008 | 0.004 |
| Research integrity | 0.034 | 0.047 |
| Insufficient payload (model declined to judge) | 0.010 | 0.010 |
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".