Re-evaluating gypsum vein formation and strain history along the Caprock Escarpment
Bibliographic record
Abstract
Mineral veins are of high importance because they display evidence of fluid migration networks, providing insight for fluid and mineral movement in rocks and reservoirs. Gypsum vein formation occurs as a biproduct of hydrofracturing and precipitation processes, as the diffusion of subsurface fluids into the fracture allows for the oversaturation of calcium sulfate ions to occur and precipitate as gypsum. Importantly, mineral fibers formed in gypsum veins can provide the direction of extension during vein formation and the growth history of gypsum fibers. \n\nThe Palo Duro Basin, a sedimentary basin formed within Texas during the Late Pennsylvanian to the Permian, has been undergoing salt dissolution and subsidence since the Permian. Early studies within the Palo Duro Basin correlated salt dissolution with gypsum vein formation. This study reevaluates the mechanisms for gypsum vein formation and provides a new model for formation of gypsum veins within the sandstones and siltstones of the Permian-Triassic Lower Quartermaster, and the Permian Cloud Chief Gypsum and Whitehorse Sandstone along the east side of the Caprock Escarpment of the Palo Duro Basin. During vein formation, calcium sulfate saturated fluids fill preexisting fractures following subsidence of underlying salt beds. Gypsum will precipitate, forming gypsum veins. Hydraulic pressure will then further the formation of gypsum veins, resulting in new veins formed from the preexisting fractures. Grain size controls the formation and localization of fluid movement, and thus, the formation of gypsum veins. Gypsum vein density has an inverse relationship with the amount of clay present in a given unit. Lithostatic loads have changed throughout the formation of gypsum veins, with present day over burden pressures on the edge of the Caprock Escarpment similar to loads during the Permian.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".