Geologically constrained gravity inversion for the Voisey's Bay ovoid deposit
Bibliographic record
Abstract
Constructing a general, three-dimensional model of the subsurface density distribution by minimum-structure, or Occam-style, inversion of gravity data has been practical now for several years. The usual approach is to seek a model that is simple in the sense of having the least amount of spatial variation while still reproducing the observations (hence the description “minimum-structure”). This has the advantage of generating models with few, if any, fictitious features. However, often the models produced bear only a gross, diffuse resemblance to geology. It has been recognized since the inception of the minimum-structure inversion technique that geological information can be incorporated by seeking a model that is simple in the sense of being as close as possible to a reference model while still fitting the observations. This is rarely done, often because insufficient geological information is available, or because inversion of geophysical data is no longer thought to be useful once a target has been found and drilling begun. Here we summarize a study demonstrating how models constructed using a minimum-structure inversion procedure can be influenced and constrained by reference models derived from downhole physical properties.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".