Kimberlites and the mantle sample - can we decode their geotectonic message?
Bibliographic record
Abstract
Although studies of kimberlites and their mantle-derived inclusions still convey contradictory geotectonic messages (the models of diamond genesis by Haggerty (1986) and Schulze (1986) are two recent examples), geotectonic information derived from such studies should ultimately fit into compatible upper mantle models that can be integrated with those from other Earth science disciplines.Tectonic aspects of kimberlites and related rocks involve their local and regional structural settings, their larger-scale geotectonic controls, the physical processes controlling kimberlite formation in the upper mantle, and the ascent through the lithospere.Inclusion studies (involving xenoliths, megacrysts, and diamonds thought to have equilibrated under upper mantle conditions) yield information about the composition, physical conditions of formation, textures, and structures of small isolated samples that are combined to obtain a picture of the composition, physical conditions, structure, and origin of the lithospheric column traversed by the kimberlite.Viewed in this context, geotectonic bits of information from kimberlite and inclusion studies can be divided into those contributing to the understanding of processes of upper mantle formation and those monitoring later modifications of the mantle.As the mantle evolves continuously, such categories naturally are end members of a continuous spectrum of processes.However, the division makes sense for diamondiferous kimberlite provinces on Precambrian shields, where the subcontinental lithosphere, from which most of the mantle sample was derived, was assembled in Early Precambrian times, whereas the kimberlite eruptions and other intraplate magmatism were triggered by distinctly later events.
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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 | 0.003 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".