Diamond exploration and prospectivity of Greenland. Gov Greenland Department of Geology Record 1, 228 pp.
Bibliographic record
Abstract
Greenland is dominated by cratonic blocks that provide conditions for the formation of diamonds. Pre-1.6 Ga rocks are exposed over 43% of ice-free land and many basins in younger areas evidence underlying Archean basement. Studies of mantle xenoliths reveal thick mantle lithosphere to 220 km in the North Atlantic Craton of western Greenland. Kimberlites, ultramafic lamprophyres and lamproites are known to be exposed abundantly, and span 1632 Ma of geological time. With carbonatites, 3029 discrete bedrock diamond-prospective occurrences have been identified. Known diamondiferous bodies are well represented over Greenland’s west coast, most notably the Garnet Lake 4 metre-thick composite aillikite / kimberlite sheet at Sarfartoq, and aillikite sheets at Qeqertaa, Disko Bay. Data from these, and other localities, demonstrate the potential for Greenland to host diamondiferous bodies with large, good quality diamonds in potentially economic concentrations. While preserved pipes may be discovered at higher elevations, the rarity of known pipes and diatremes evidences extensive glacial erosion and raises the potential for offshore and paleoplacer deposits. The Government of Greenland’s Diamond exploration data package is used to conduct a regional diamond prospectivity analysis. Most prior exploration targeted diamond indicator minerals in alluvial and glaciogenic samples averaging 10 kg in weight, and with inspection of recovered indicators concluding that sampling strategies have been adequate. Indicator minerals, including garnet, all reveal mineral chemistries consistent with deep mantle sources, often within the diamond stability field, and ilmenite compositions often support very high diamond preservation. All geographic subdivisions overlap chemistries of indicators from diamond-producing areas of Canada. The North Atlantic Craton of West Greenland and the Ketilidian Orogen of southern Greenland show particularly consistent diamond-prospective chemistries, while the Rae Craton of western Greenland is more variable. Quantitative prospectivity modelling incorporating geophysical data emphasises the importance of these regions but also highlights potential in the under-explored Inglefield Orogen and North Atlantic Craton of eastern Greenland. Historical data, compared with more regional, indirect prospectivity metrics show that further opportunities for diamond exploration exist in Greenland in selected areas of the west coast, as well as within less-explored areas such as eastern and northern regions, and offshore.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".