Properties of selected soils from the sub−arctic region of Labrador, Canada
Bibliographic record
Abstract
Abstract Atotal of 212 soil profiles were described and assessed for physical and chemical properties during July 2006 as part of an Ecological Land Classification study along the Churchill River in central Labrador. Two major soil types were found in the study area along the Churchill River: Podzols and Organic soils. Podzolic soils covered approximately 60% and Organic soils occurred in 24% of the study area. Approximately 15% of the study area was classified as rock and other unconsolidated material. Summary results and a sub−set of the following soil units (from 10 soil profiles) are presented here and were distin− guished according to the Canadian System of Soil Classification (CSSC) (Soil Classifica− tion Working Group 1998): Orthic Humo−Ferric Podzol, Placic Ferro−Humic Podzol, Gleyed Humo−Ferric Podzol, Sombric Humo−Ferric Podzol, Gleyed Regosol and Orthic Luvic Gleysol. The basic properties of the soil units identified above included: (i) morpho− logical descriptions of soil profiles with differentiated horizons; (ii) field−texture tests were used to determine classes and physical properties of sands, silts, loams and occurrence of mottles; and (iii) a range of soil chemical composition of different horizons (e.g., pH, total organic carbon [TOC] and select metal concentrations) which indicated no anthropogenic contamination above background concentrations in the area.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.002 | 0.000 |
| 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".