Metasomatic iron and alkali calcic (MIAC) system frameworks: a TGI-6 task force to help de-risk exploration for IOCG, IOA and affiliated primary critical metal deposits
Bibliographic record
Abstract
Australia's and China's resources (e.g. Olympic Dam Cu-U-Au-Ag and Bayan Obo REE deposits) highlight how discovery and mining of iron oxide copper-gold (IOCG), iron oxide±apatite (IOA) and affiliated primary critical metal deposits in metasomatic iron and alkali-calcic (MIAC) mineral systems can secure a long-term supply of critical metals for Canada and its partners. In Canada, MIAC systems comprise a wide range of undeveloped primary critical metal deposits (e.g. NWT NICO Au-Co-Bi-Cu and Québec HREE-rich Josette deposits). Underexplored settings are parts of metallogenic belts that extend into Australia and the USA. Some settings, such as the Camsell River district explored by the Dene First Nations in the NWT, have infrastructures and 100s of km of historic drill cores. Yet vocabularies for mapping MIAC systems are scanty. Ability to identify metasomatic vectors to ore is fledging. Deposit models based on host rock types, structural controls or metal associations underpin the identification of MIAC-affinities, assessment of systems' full mineral potential and development of robust mineral exploration strategies. This workshop presentation reviews public geoscience research and tools developed by the Targeted Geoscience Initiative to establish the MIAC frameworks of prospective Canadian settings and global mining districts and help de-risk exploration for IOCG, IOA and affiliated primary critical metal deposits. The knowledge also supports fundamental research, environmental baseline assessment and societal decisions. It fulfills objectives of the Canadian Mineral and Metal Plan and the Critical Mineral Mapping Initiative among others. The GSC-led MIAC research team comprises members of the academic, private and public sectors from Canada, Australia, Europe, USA, China and Dene First Nations. The team's novel alteration mapping protocols, geological, mineralogical, geochemical and geophysical framework tools, and holistic mineral systems and petrophysics models mitigate and solve some of the exploration and geosciences challenges posed by the intricacies of MIAC systems. The group pioneers the use of discriminant alteration diagrams and barcodes, the assembly of a vocab for mapping and core logging, and the provision of field short courses, atlas, photo collections and system-scale field, geochemical, rock physical properties and geophysical datasets are in progress to synthesize shared signatures of Canadian settings and global MIAC mining districts. Research on a metamorphosed MIAC system and metamorphic phase equilibria modelling of alteration facies will provide a foundation for framework mapping and exploration of high-grade metamorphic terranes where surface and near surface resources are still to be discovered and mined as are those of non-metamorphosed MIAC systems.
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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 | 0.029 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.005 | 0.010 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.011 | 0.006 |
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".