Bibliographic record
Abstract
The classifi cation of granitic pegmatites was frequently attempted during the past century, with variable degrees of success and applicability. Internal structure, paragenetic relationships, bulk chemical composition, petrogenetic aspects, nature of parent medium, and geochemical features were applied. However, all schemes were marked by contemporary degrees of understanding of these parameters, and most attempts were hindered by ignoring differences in geological environment. Substantial progress was achieved only since the late 1970s. The classifi cation is approached here from two directions, based on but broadened and refi ned from earlier works by Ginsburg and Čern´y. The fi rst concept deals with geological location, leading to division of granitic pegma-tites into fi ve classes (abyssal, muscovite, muscovite – rare-element, rare-element, and miarolitic), most of which are subdivided into subclasses with fundamentally different geochemical (and in part geological) characteristics. Further subdivision of most subclasses into types and subtypes follows more subtle differences in geochemical signatures or P–T conditions of solidifi cation, expressed in variable assemblages of accessory minerals. The second approach is petrogenetic, developed for pegmatites derived by igneous differentiation from plutonic parents. Three families are distinguished: an NYF family with progressive accumulation of Nb, Y and F (besides Be, REE, Sc, Ti, Zr, Th and U), fractionated from subaluminous to metaluminous A- and I-type granites that can be generated by a variety of processes involving depleted crust or mantle contributions; a peraluminous LCT family marked by prominent accumulation of Li, Cs and Ta (besides Rb, Be, Sn, B, P and F), derived mainly from S-type granites, less
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".