Bibliographic record
Abstract
Abstract Four main paradigms exist in diamond geology at this time: (1) Diamonds are related only to kimberlites; (2) Diamondiferous kimberlites can only form within ancient, Archean cratons; (3) Diamondiferous kimberlites can only form within the thickest lithospheric blocks of cratons; and (4) Natural diamonds are formed only in ultra high-pressure environments. The existing data demonstrate that these paradigms are not always correct. Primary, diamondiferous kimberlites can occur not only within Archean cratons, but also within collisional belts of different types and within epicratonic, essentially ensialic orogenic belts. In addition, there are numerous occurrences of igneous, non-kimberlitic, diamondiferous rocks which include representatives of the following groups: (I) Volcanic rocks: lamproites, lamprophyres, picrites, meimechites, and alkali-basalts. (II) Plutonic rocks: peridotites and pyroxenites. There are non-kimberlitic rocks which may contain economic diamond mineralization. Although, the ultramafic rocks are likely to contain a lower-grade of diamond mineralization, than the volcanic rock-types. However, such types of mineralization can produce medium sized and, probably, large alluvial placer deposits. The existing criteria for prospecting and preliminary evaluation of primary diamond deposits, based on ‘ traditional’ experience in cratonic areas, is therefore non-applicable in prospecting for new types of diamond deposit.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".