Evaluating the quality of bed length and area balance in 2D structural restorations
Bibliographic record
Abstract
Abstract The use of structural restorations as a tool to investigate structural evolution, fault and horizon relationships, and validity of interpretation has been widespread for more than four decades. The first efforts relied on hand-drafted bed-length measurements of commonly constant thickness stratigraphic units and were typically applied to fold-and-thrust belt settings. The advent of computer-assisted section construction and restoration software allowed for the assessment of more complicated structural interpretations by applying several new methods for forward and inverse strain transformation. Although quicker and more accurate than hand-drafted, the results of computer-aided structural modeling still need to be interrogated. We have reviewed the different strain transformation (restoration) methods available and their implications for bed length and area conservation: (1) fundamental simple shear and its two basic modes (flexural slip and inclined shear inversions), (2) fault-related folding techniques, and (3) the effects of mechanical stratigraphy and compaction. The assessment of the restoration methods was illustrated by examining two examples: the Mount Crandell Duplex Structure in southern Alberta and the Virgin River Extensional Basin in the southeast of Nevada. For both examples, we developed tables listing and confirming the deformed/restored state line lengths and areas. We believe that such tables should be provided for any strain transformation exercise, along with the restoration results as parameters for quality control, to prevent over- and underestimations that deviate more than 5% from the initial interpretation.
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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 | 0.002 | 0.004 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".