Ground conductivity measurements at selected National Wildlife Refuges, Montana and North Dakota, 2017-2018
Bibliographic record
Abstract
Shallow subsurface electrical conductivity was mapped at selected U.S. Fish and Wildlife Service managed lands in northeast Montana and northwest North Dakota using the DUALEM421 electromagnetic sensor (Dualem, Inc., ON, Canada) in the winters of 2017 and 2018. Data were acquired by towing the DUALEM421 sensor on a sled behind an all-terrain vehicle or snow machine, with the sensor at a nominal height of 0.3 meters (m) above ground surface. Approximately 427 line-kilometers (km) of data were acquired over an area of nearly 26 square-kilometers. Data were manually edited to remove sensor dropouts, lag corrected for apparent offsets between recorded GPS location and data locations for each coil pair, and averaged to a sounding distance of 1m along the survey path; data were not decoupled from infrastructure noise sources (powerlines, pipelines, fences, etc.) or corrected for sensor pitch or roll. This data release contains raw and processed electromagnetic data. Digital data are described by the data dictionaries. Additional details regarding the processing steps are described in the metadata.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.007 |
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".