Symposium no. 31 Paper no. 1365 Presentation: oral 1365-1
Bibliographic record
Abstract
Land settlement and agriculture in western Canada began in the late-1800s, and has been mainly a 20 Century development to which Soil Science has made substantial contributions. Some of the first scientific observations of land by early explorers dealt with land suitability for agriculture and included astute observations about soils. The rapid increase in settlement and cultivation in the first two decades of the 20 century resulted in the initiation of research by federal Department of Agriculture, and the start of Soil Science departments at the universities in the 1920s. Soil scientists over the next several decades contributed to better agronomy, improved soil conservation, soil survey and soil classification, as Soil Science matured as a discipline. Soil Science in universities and government research institutions through the 1960s and `70s was considered strong, and relevant to the issues of the day. Declines in funding, especially base funding, and perceptions that tasks such as soil survey were largely complete resulted in a decline in the late 1980s and `90s, Soil scientists themselves must assume some of the responsibility for the decline, as they became more specialized and inward looking, failing to connect with those making decisions about land use. The several years, however, has resulted in an increased interest in our science as issues such as global change point to the interconnectedness of soil, water and air systems and the central place of soils. It is important that soil scientists continue to do good science, but also be proactive and straightforward in relating their work to issues of the day, giving our science the place it must assume to remain pertinent in future.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 0.013 |
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; both teacher heads agree on what is shown here.
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".