A Geologic Rock Garden as an Artificial Mapping Area for Teaching and Outreach
Bibliographic record
Abstract
The St. Mary's Cement Rock Garden, located on the campus of the University of Western Ontario (London, Ontario, Canada), provides a compact and easily accessible area where geological features can be observed on an outcrop-scale. We describe how this hands-on facility provides students and visitors with a more realistic sense of geologic principles than does a traditional laboratory-based environment.Rock slabs and boulders are arranged in a confined space on our university campus to simulate a geologic mapping area. Here, rock types can be identified, stratigraphy interpreted, structures measured, rock boundaries mapped, and geologic history reconstructed. Paved walkways dividing garden segments conveniently serve as the locations of faults and unconformities. Vegetation has been incorporated in the rock-garden design to enhance the natural appearance of the setting.Students and visitors are encouraged to climb on the rocks to closely examine them as a professional geologist would in the field. By doing so, students play an active role in learning about geology, gain confidence and a better understanding of the large-scale spatial relations of rocks, and gain insights into geologic processes – aspects that are often difficult to convey indoors. The artificial mapping area has proven effective for demonstrating field techniques to students prior to their first field trip or camp. Using examples of real bedrock excavated from surrounding areas is also a unique way for visitors to gain a better appreciation of geologic materials, their uses, and the natural environment of their region.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.037 | 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".