Bibliographic record
Abstract
Abstract In March/April 2011 Apache carried out an extensive series of seismicacquisition tests in Cook Inlet, Alaska, to evaluate the feasibility oflarge-scale, year-round 3D seismic acquisition in Cook Inlet, and to look atthe effectiveness of a nodal or autonomous seismic recording system compared toa conventional cable-telemetry system. An 18-mile seismic line startingonshore, crossing the tidal mudflats, and extending into the deeper water ofCook Inlet was acquired using multiple onshore and offshore source, receiver, and instrument types to establish the viability of a large-scale regional 3Dsurvey and the optimum source parameters for such a program. The location ofthe test line is shown in Figure 1. Background Alaska's Cook Inlet Basin is a proven hydrocarbon-producing compressionalfore-arc basin with 1.3 billion barrels of oil and 8 TCF of gas produced, andapproximately 1 billion barrels of oil and 21 TCF of gas yet to be found, according to the USGS and BOEM. Since the expansion of exploration andproduction activity on Alaska's North Slope in the 1980's there has been littleexploration activity in Cook Inlet; small 2D and 3D seismic surveys havegenerated leads for the small number of wells drilled in the area during thistime. The majority of these seismic surveys had been either exclusively onshoreor offshore, with only a handful of transition zone surveys crossing theshoreline, and all acquired in the short window of a single season. To makelarge-scale regional seismic surveying a reality, a single crew, equipped tooperate year-round, would be needed.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.002 | 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; both teacher heads agree on what is shown here.
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".