Hills thought to be mountains: A geobiocultural characterization of island highlands in Canada's continental plain
Bibliographic record
Abstract
Abstract North America is characterized by an expansive continental plain that has been described as platter‐flat. Yet this central continental plain includes isolated uplands that some people call mountains. The hill‐mountain muddle is a classic problem of geomorphology, arising from the challenge of discriminating continuous, attached forms. Here we approach this problem initially by using crisp, terrain‐only classification approaches. We overlay a global mountain classifier with a plain and prairie designation to identify 20 mountains in Canada's continental plain, then apply a landform classification tool to delineate their spatial extents and to locate adjacent, equal‐area lowlands. We then characterize and compare the attributes of uplands and adjacent lowlands with 15 geobiocultural indicators reflective of the intersections of land, life, and people. Supporting our hypothesis that small, isolated uplands in the continental plain have distinctiveness disproportionate to their dimensions, the 20 uplands are indeed modest in elevation, prominence, and isolation, but distinct in geobiological characteristics relative to adjacent lowlands. The geobiocultural distinctiveness of uplands in the plain relative to surrounding lowlands causes these local prominences to stand out, to seem higher than they are, and to be hills described or named as mountains.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".