Introduction to the Special Issue Devoted to Alkalic Porphyry Cu-Au and Epithermal Au Deposits
Bibliographic record
Abstract
This special issue is devoted to alkalic porphyry Cu-Au andepithermal Au deposits and focuses on two regions: BritishColumbia, Canada (Fig. 1), and the Southwest Pacific region(Australia and Papua New Guinea: Fig. 2). The special issuecommences with a review of Triassic to Jurassic metallogenyof British Columbia (Logan and Mihalynuk, 2014), then documentsore zones from several alkalic deposits (Central zone,Galore CreekMicko et al., 2014; Southwest zone, GaloreCreekByrne and Tosdal, 2014; Northeast zone, Mt. PolleyPass et al., 2014; Lower Main zone, LorraineBathet al., 2014; Mt. MilliganJago et al., 2014) and provides acomprehensive overview of mineralization in the Lorrainedistrict (Devine et al., 2014). Four contributions documentalkalic porphyry and epithermal deposits in New South Wales(NorthparkesHarris and Holcombe, 2014; Endeavour 41Zukowski et al., 2014; Endeavour 42Henry et al., 2014;CadiaHarris et al., 2014). The final contribution uses theresults of mapping and core logging in order to resolve thephysical volcanology and hydrothermal evolution of the giantLadolam alkalic epithermal gold deposit, Papua New Guinea(Blackwell et al., 2014). Eight of these papers are the outcomeof a collaborative project between the Mineral DepositResearch Unit (MDRU) at the University of British Columbia,the Australian Research Councils Centre for Excellencein Ore Deposits (CODES) at the University of Tasmania, andindustry partners. The remaining are based on work by theBritish Columbia Geological Survey (Logan and Mihalynuk,2014), Teck Resources Ltd. (Devine et al., 2014), a researchcollaboration between CODES and Newcrest Mining Ltd.(Harris et al., 2014), and the University of Queensland (Harrisand Holcombe, 2014).
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.101 | 0.038 |
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".