Tracking rapid landscape change with repeated photography, Gros Morne National Park, Canada
Bibliographic record
Abstract
At various coastal and inland sites in and around Gros Morne National Park in western Newfoundland, photographs taken periodically over many decades illustrate the physical stability of landforms. ἀese images provide a convenient, qualitative way to track the development of stone rings and patterned ground, the movement of rocks along intertidal platforms, changes to marine estuaries and to alluvial rivers and fans, temporal trends in late-lying snow beds along mountain tops, and slope failure by landslides and rock falls. ἀis study has established a spatial and temporal photographic record of slope failures along the steep cliḀs of Western Brook Pond, showing that nearly all of the sites identiᴀed in earlier studies as high risk of failure have remained stable. In contrast, thin-skinned landslides along Winter House Brook have remained active for at least 100 years. Little evidence of physical changes in patterned ground features in Trout River Gulch was found, other than frost-heaving in soils disturbed by road construction. Fluctuations from year to year in the level of gravel beaches along parts of the coast are common, and blow-outs continue to modify coastal sand dunes. Apart from certain engineered sites where change was obviously driven by direct human activities, the immediate cause or “driver” of change was natural (non-human), the result of gravitational instability, heavy precipitation, wave and storm action, frost heaving, and other background processes of the sort that long pre-date the coming of people to the region. Continuation of this kind of inexpensive, non-invasive monitoring can assist in assessing ecological integrity, managing public safety, and interpreting landscape processes for Park visitors.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 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) | 0.004 | 0.001 |
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".