Picture-Perfect Petrography: Affordable Thin-Section Scanning for Geoscientists in the Digital Era
Bibliographic record
Abstract
Research Article| September 29, 2023 Picture-Perfect Petrography: Affordable Thin-Section Scanning for Geoscientists in the Digital Era Derek D.V. Leung; Derek D.V. Leung § Harquail School of Earth Sciences, Laurentian University, 935 Ramsey Lake Road, Sudbury, Ontario P3E 2C6, Canada § Corresponding author e-mail address: dleung@laurentian.ca Search for other works by this author on: GSW Google Scholar Andrew M. Mcdonald Andrew M. Mcdonald Harquail School of Earth Sciences, Laurentian University, 935 Ramsey Lake Road, Sudbury, Ontario P3E 2C6, Canada Search for other works by this author on: GSW Google Scholar Author and Article Information Derek D.V. Leung § Harquail School of Earth Sciences, Laurentian University, 935 Ramsey Lake Road, Sudbury, Ontario P3E 2C6, Canada Andrew M. Mcdonald Harquail School of Earth Sciences, Laurentian University, 935 Ramsey Lake Road, Sudbury, Ontario P3E 2C6, Canada § Corresponding author e-mail address: dleung@laurentian.ca Publisher: Mineralogical Association of Canada Received: 20 May 2023 Accepted: 05 Jun 2023 First Online: 14 Aug 2023 The Canadian Journal of Mineralogy and Petrology (2023) 61 (5): 1045–1050. https://doi.org/10.3749/2300038 Article history Received: 20 May 2023 Accepted: 05 Jun 2023 First Online: 14 Aug 2023 Cite View This Citation Add to Citation Manager Share Icon Share Facebook Twitter LinkedIn Email Permissions Search Site Citation Derek D.V. Leung, Andrew M. Mcdonald; Picture-Perfect Petrography: Affordable Thin-Section Scanning for Geoscientists in the Digital Era. The Canadian Journal of Mineralogy and Petrology 2023;; 61 (5): 1045–1050. doi: https://doi.org/10.3749/2300038 Download citation file: Ris (Zotero) Refmanager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentBy SocietyThe Canadian Journal of Mineralogy and Petrology Search Advanced Search Digital imaging of thin sections is an integral part of contemporary geoscience research. Images taken under the petrographic microscope (i.e., photomicrographs) capture mineralogical and textural features—e.g., modal mineralogy, grain size, and fabrics—that can be quantified and interpreted via digital image analysis. However, it can be challenging to capture all the features present in a full thin section, owing to the limited field of view that is possible on a standard petrographic microscope (∼5 mm). These areas can be imaged under the microscope and stitched together into image mosaics (i.e., image mosaicking), but this is... You do not have access to this content, please speak to your institutional administrator if you feel you should have access.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.247 | 0.102 |
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".