A precise and refined identification method for carbonate bioreefs and prograding bodies guided by a knowledge graph
Bibliographic record
Abstract
Abstract Carbonate bioreef formations serve as crucial hydrocarbon reservoirs, and their accurate identification bears significant implications for oil and gas exploration. Moreover, the precise and refined delineation of prograding body structures aids in the comprehensive analysis of stratigraphic geologic configurations. We develop the knowledge graph and geologic strata interpolation constraints (KGGSICs) model for the intricate identification of carbonate bioreefs and prograding body structures. Furthermore, we assess our KGGSIC-Unet architecture on the Dengying Formation Sections 3-4 carbonate bioreefs and prograding bodies in the Moxi area of the Sichuan Basin. Experimental results indicate that the KGGSIC enhances the predictive performance of the U-Net and realizes the precise and refined segmentation of carbonate bioreefs and prograding body structures. In addition, through a meticulous geologic study of the area, we synthesize the 2D profile identification results to achieve the precise and refined identification of carbonate bioreefs and prograding bodies.
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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) | 0.000 | 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".