Soil science at the University of Alberta: a century of service to science and society
Bibliographic record
Abstract
This paper highlights major activities and achievements in soil science by professors at the University of Alberta (U of A), which provide incredible benefits to society, provincially, nationally, and globally. Evolution of the soils profession in Alberta commenced in 1919 with the hiring of F.A. Wyatt, who developed the Department of Soil Science (DSS) and initiated a soil survey program in Alberta. J.D. Newton joined the department in 1922, teaching and supporting soil surveys that led to a fertilizer program greatly benefitting agriculture. With time, opportunities and problems were encountered with utilization of soils. U of A soil scientists conducted inventories, conducted innovative research, developed superior management techniques, and through evolving education and extension, continuously helped bring improvements to how we utilized and managed soil resources. The DSS 100 yr evolution is chronicled under the themes of pedology (including soil survey), soil fertility, soil sustainability (conservation, land reclamation, and contaminant remediation), with embedded specialized studies within these themes.
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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.015 | 0.013 |
| Scholarly communication | 0.018 | 0.003 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.020 | 0.003 |
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".