Remote predictive mapping of the Boothia mainland area, Nunavut, Canada: an iterative approach using Landsat ETM, aeromagnetic, and geological field data
Bibliographic record
Abstract
An iterative remote predictive mapping approach was applied in regional-scale bedrock mapping of the Boothia mainland area, Nunavut, Canada. A geological interpretation of high-resolution airborne magnetic, Landsat Enhanced Thematic Mapper (ETM), and legacy field data resulted in a provisional remote predictive map (RPM) that was used to guide regional bedrock mapping in the summer of 2005. After the newly acquired field data were incorporated in the geoscience database, the provisional RPM was upgraded to 1 : 250 000 scale geological maps in a second iteration of geological interpretation. In general, the RPM was much better at predicting where major changes in lithology occurred than at predicting specific rock types. A comparative assessment of the generalized units of the RPM and geological maps at field stations yields an overall agreement of 82.3%. The number and dimensions of supracrustal belts on the RPM, however, were exaggerated and showed a relatively low agreement of 31% with geological map units at the field stations. This is explained by the confusion between supracrustal belts and metaplutonic units being both associated with high-spatial frequency linear and low-relief magnetic anomaly patterns. Field observations confirm that linear high-spatial frequency magnetic anomaly patterns in metaplutonic units are induced by metamorphic new growth of magnetite. These magnetic anomaly patterns parallel curvilinear features extracted from Landsat imagery and foliation strike measurements to the extent that regional fold structures can be reliably traced throughout the survey area. Spectral absorption features of carbonate in Landsat ETM band 7 and the overall high albedo of quartzite and marble allow differentiating Paleoproterozoic supracrustal units from their carbonate- and quartzite-barren Archean counterparts.
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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 | 0.001 | 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 | 0.001 | 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".