Application of Innovative Geochemical and Mineralogical Techniques to Understanding the La Victoria Epithermal Gold Deposit, Peru
Bibliographic record
Abstract
Journal Article Application of Innovative Geochemical and Mineralogical Techniques to Understanding the La Victoria Epithermal Gold Deposit, Peru Get access Kelsey L Rozon, Kelsey L Rozon Department of Earth Sciences, Western University, London, ON, Canada Search for other works by this author on: Oxford Academic Google Scholar Neil R Banerjee, Neil R Banerjee Department of Earth Sciences, Western University, London, ON, Canada Corresponding author: neil.banerjee@uwo.ca Search for other works by this author on: Oxford Academic Google Scholar Lisa L Van Loon, Lisa L Van Loon Department of Earth Sciences, Western University, London, ON, CanadaLISA CAN Analytical Solutions Inc., Saskatoon, SK, Canada Search for other works by this author on: Oxford Academic Google Scholar Bill Pearson Bill Pearson Eloro Resources Ltd., Toronto, ON, Canada Search for other works by this author on: Oxford Academic Google Scholar Microscopy and Microanalysis, Volume 25, Issue S2, 1 August 2019, Pages 800–801, https://doi.org/10.1017/S1431927619004732 Published: 01 August 2019
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 | 0.001 |
| 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".