Lithium exploration, geologic modelling, resource estimation and mine planning for a spodumene-bearing pegmatite deposit in Ontario, Canada
Bibliographic record
Abstract
DMT GmbH Co. KG, Germany <br> The growing need for energy storage for e-mobility and other battery-intense applications has created a large interest in the key battery commodity lithium (Li). A recent hard rock lithium exploration and evaluation project is being conducted at Georgia Lake in Ontario, Canada. The Georgia Lake pegmatites contain Li- and rare metals-bearing spodumene in the area. In addition, previous work also identified beryl, columbite, molybdenite, amblygonite, apatite, and bityite, enhancing the Li and rare metals potential of the area. The recent investigation focuses on the area where several spodumene-bearing pegmatites occur at the surface. Their length at the surface is between 50 m and 1.8 km along strike and 1-10 m width. More than 200 boreholes were drilled with a spacing below 50 m. The drill holes hit the pegmatites in a maximum depth of 350 m below surface, but continuation towards depth is expected. The varying Li2O content of the retrieved core samples reaches up to 2.7%. The majority of the pegmatites are hosted by metasediments or biotite-rich granite. The internal zonation of the pegmatite dykes is in general characterized by a granitic or aplitic border zone with a spodumene, albite and quartz central zone. In some cases aplite layers and quartz tourmaline veins occur. Mineralisation consists of coarse-grained fresh pale green spodumene crystals oriented perpendicular to the strike of the dyke. In some areas, the length of these crystals reaches up to 1 m and a thickness of up to 12 cm. Five main pegmatite bodies have been newly modelled and a resource assessment made. The NI43-101 compliant technical report shows a measured resource of 1.89 million tons (Mt) @1.04% Li2O, an indicated resource of 4.68 Mt @1.00% Li2O, and an inferred resource of 6.72 Mt @1.16% Li2O. To extract these resources, the initial mine planning foresees open pit excavation of the top parts combined with underground sublevel stoping with backfilling of the deeper deposit.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".