Thermal contraction crack polygons in Nunavik (northern Quebec): Distribution and development of polygonal patterned ground
Bibliographic record
Abstract
Abstract We evaluated the spatial distribution and morphological variability of thermal contraction crack polygon (TCCP) networks across Nunavik, a 440,000‐km2 region of northern Québec that spans the northward transition from discontinuous to continuous permafrost. A population of 4,567 TCCP sites was sampled and analyzed from 80,737 georeferenced high‐resolution aerial photographs and 264,504 km2 of ESRI satellite basemaps. For each site, six parameters were inventoried and compiled into a database: (a) network geometric arrangement; (b) intersection angles; (c) number of subdivisions and nested polygons (referred to as generations of development); (d) dominant polygon morphology; (e) surficial geology; and (f) vegetation cover. Statistical analyses of the tabulated data revealed a strong association between Holocene glacial, glacio‐fluvial, fluvial, marine, and organic landforms and the different intersections angles in the networks, providing insight into how the processes of thermal contraction cracking function and manifest geomorphically across varied permafrost landscapes. Orthogonal polygons (intersection angle of 90°) dominate on flat terrains where the thermo‐mechanical stresses are probably spatially homogeneous. Hexagonal (angles of 120°) and poorly structured polygons tend to form where topography variability probably generates heterogeneous heat flow patterns and thermo‐mechanical stresses in the ground, resulting in irregular cracking patterns.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".