Supplemental Material: Structural styles and kinematic evolution of the Front Ranges of the Southern Canadian Rockies
Bibliographic record
Abstract
Included in the supplement are details of how we calculated the error for the data presented in our scatterplot, along with seven additional figures. One is additional examples of our binning and fold analysis procedure and the results on three cross sections (m–m′ [51.06467°N, 115.586°W], [51.08187°N, 115.554°W]), n–n′ [50.92633°N, 115.132°W], [50.94936°N, 115.089°W], and o–o′ [51.05612°N, 115.446°W], [51.09349°N, 115.377°W]); palimpsestic restorations of our regional cross sections; high-resolution plates of our compiled geologic maps and associated cross sections; a map of our study area highlighting the bounds of maps we used to create our compiled map; a map of our study area detailing the bounds of our various digital elevation models; an example of our dynamic binning process from the data shown in Figure 5; regional cross sections with strike and dip data projected from 1 km away; and a comparison between different data collection methods. The remotely acquired strike and dip data are available on StraboSpot (https://strabospot.org/). Any GIS files needed to construct any of our geologic map figures in this study are available by emailing the corresponding author.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.430 | 0.047 |
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".