Structurally controlled hydrothermal alteration of carbonate reservoirs: Introduction
Bibliographic record
Abstract
Langhorne “Taury” Smith heads the Reservoir Characterization Group at the New York State Museum. He holds a B.S. degree from Temple University, a Ph.D. from Virginia Tech, and did postdoctoral work at the University of Miami. He also worked for Chevron as a development geologist, and current research interests are focused on carbonate reservoir characterization and hydrothermal alteration of carbonate reservoirs. Graham Davies received his B.Sc. (honors) degree and Ph.D. from the University of Western Australia. His doctoral thesis was on modern carbonates in Shark Bay, Western Australia (published in AAPG Memoir 13). After a postdoctoral fellowship with James Lee Wilson at Rice University, he joined the Geological Survey of Canada (GSC) in Calgary. After 7 years with the GSC, Graham co-founded and became principal owner of AGAT (Applied Geoscience and Technology) Consultants/Laboratories. Since 1983, he has operated through GDGC Ltd. He has published about 70 papers on the geology of Australia and Canada, and has authored or coauthored more than 600 consulting reports. Graham received the CSPG Douglas Medal in 2002 for his work on Arctic Paleozoic carbonates and evaporites, and on the Triassic and other aspects of western Canadian geology. His principal current interest is in hydrothermal dolomites. This issue of the AAPG Bulletin is dedicated to structurally controlled hydrothermal alteration of carbonate rocks and reservoirs. This type of alteration covers the spectrum of carbonate-hosted sulfide ore deposits to hydrothermal dolomite to leached limestones, and in many cases has a major impact on reservoir type, geometry, quality, and distribution. Hydrothermal dolomite (HTD) reservoirs have a long history of exploration and development in North America, extending from the earliest discoveries in the Ordovician Lima-Indiana and other trends of the northeastern United States (Hurley and Budros, 1990; Wickstrom et al., 1992), and continuing today with the Trenton–Black River play …
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".