One-dimensional inversion of airborne time-domain \nelectromagnetic data from Taylor Brook, western Newfoundland, \nand 3D finite-element time-domain forward modeling using \nunstructured grids
Bibliographic record
Abstract
In this thesis, geophysical inversion and numerical modeling are carried out on a dataset collected \nusing the Airborne Time-Domain Electromagnetic (ATEM) survey method over an area called \nTaylor Brook, western Newfoundland, which potentially hosts massive sulfide mineralization. \nATEM profiles are interpreted using a 1D inversion code (EM1DTM). The inversion results \nindicate that the majority of the dataset collected in the part of the area which does not show any \nanomaly is highly noise-contaminated. In contrast, several observation points near the sulfide \nmineralization have reasonable anomalies. For a better understanding of the sulfide-bearing zone’s \ndip, thickness and depth in the survey area, 2D cross-sections along each profile are created by \ncombining 1D models for each observation point. Also, 3D forward modeling is applied to several \nEarth models that are created using the information of boreholes and the results of 1D inversions. \nFor 3D modeling of time-domain EM problems, the finite-element time-domain (FETD) method \nusing unstructured tetrahedral meshes is used. The dataset for two different survey profiles that \nhave boreholes nearby were chosen to guide the building of the 3D models. A trial-and-error \nmethod, in which the physical properties and thicknesses of the geological structures were varied, \nresulted in a reasonable match between the vertical component (z-component) of the calculated \nresponses from the FETD forward modeling and the measured data. This reasonable match would \nmean that the final Earth model is reasonable representation of the subsurface in the survey area.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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 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".