Southeast Slave Craton Lithosphere, Revisited
Bibliographic record
Abstract
We have re-investigated the mantle lithosphere of the southeast Slave Craton by integrating new, and compiled mantle xenocryst (Griffin et al. 2004) and xenolith (Kopylova and Caro 2004) datasets.Kimberlites examined include Gahcho Kué-5034, CL25, CL174, and Snap Lake.Gahcho Kué 5034, Hearne, and Tuzo pipes are currently mined for diamonds, Snap Lake is a past-producing mine, and CL25 and CL174 are not considered to be economic.EPMA data for Cr-diopside and garnet were obtained at the University of Alberta.FITPLOT (Mather et al. 2011) geotherms were generated utilizing Cr-diopside pressure-temperature (P-T) data determined for Gahcho Kué-5034, CL25, and CL174 (Table 1) via singleclinopyroxene thermobarometry (Nimis and Taylor 2000).Mantle xenolith P-T data was also utilized to generate a FITPLOT geotherm for Gahcho Kué-5034.Xenolith and Cr-diopside FITPLOT geotherms for Gahcho Kué-5034 are within uncertainty of each other yielding a lithospheric thickness of ~ 230 km (Table 1).Neither Cr-diopsides, nor mantle peridotites were observed in any heavy mineral concentrates for Snap Lake for samples from this study.Given that the four studied kimberlites are within a limited geographic area (20 x 100 km) in the southeast Slave Craton and are of approximately the same age (542 -523 Ma;Heaman et al., 2004), we have utilized the FITPLOT geotherm from the CL25 kimberlite as a proxy for Snap Lake when examining garnet temperature -depth profiles.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".