INNOVATIVE METHODOLOGY FOR DETECTION OF FRACTURE-CONTROLLED SWEET SPOTS IN THE NORTHERN APPALACHIAN BASIN
Bibliographic record
Abstract
The primary goal was to enter Phase 2 by analyzing geophysical logs and sidewall cores from a verification well drilled into the Trenton/Black River section along lineaments. However, the well has not yet been drilled; Phase 2 has therefore not been accomplished. We have switched oil and gas exploration and production companies, and are now in continued negotiations with Fortuna concerning a plan to retrieve 18 m of horizontal core across a gas-charged zone in the Trenton/Black River in central New York State, the ''hottest'' play in the Appalachian Basin. We completed analysis of remote sensing images to determine, by using the weights-of-evidence method, which images and processing techniques result in lineaments that best reflect the fractures found in outcrop. The conclusions do not differ from the preliminary conclusions reported in the previous progress report. These data continue to demonstrate that integration of aeromagnetic and remote sensing lineaments, surface structure, and soil gas and seismic allows us to extrapolate Trenton-Black River trends away from confirmatory seismic lines.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".