Mapping of apparent magnetic susceptibility and the identification of fractures: A case study from the Eye-Dashwa Lakes pluton, Atikokan, Ontario
Bibliographic record
Abstract
Abstract In situ magnetic-susceptibility measurements are only possible on outcrops, which are often limited by overburden and water bodies. An alternative approach is to derive an apparent susceptibility map from total-magnetic-intensity (TMI) surveys, which was done in this study for the Eye-Dashwa Lakes pluton near Atikokan, Ontario. Susceptibility logs of cores directly link alteration to systematic changes in the amount and composition of magnetic minerals. The surficial distribution of alteration zones was originally estimated from a limited number of in situ magnetic-susceptibility measurements. Here, through forward modeling of the TMI data set, susceptibility data are used to validate the apparent susceptibility data set. The modeling accounts for the bathymetric surface of all lakes that cover the area. A two-step process of bulk and local-scale modeling was used to estimate apparent susceptibility patterns. Bulk magnetic susceptibility is used as an indicator of overall alteration content, and local-scale apparent magnetic-susceptibility values are computed using a forward-modeling routine. The new apparent magnetic data set indicates northwest and northeast linears, which are the same as those seen in previous studies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".