Bibliographic record
Abstract
Compared with many other countries in the Organization for Economic Cooperation and Development (OECD), and particularly with the United States, Canada has suffered serious agriculture-related resource degradation problems only in recent decades (Stonehouse 1994). This is true especially of eastern Canada, where agriculture was characterized by mixed livestock-cropping systems and long crop rotations with a high proportion of forage and cereal grain crops until the early 1960s. Since then, pervasive technological progress and intensification of production techniques have led to increasing specialization, separation of livestock from cropping enterprises, shorter crop rotations, and greater dependence upon off-farm inputs such as synthetic pesticides, fertilizers, feed additives, and animal hormones (Kay and Stonehouse; Miller et al.). In turn, these trends have resulted in severe natural resource degradation problems, epitomized by erosion and compaction of soils and pollution of waterbodies by sediment, plant nutrients, pesticide residues, and bacteria from livestock manure (Dumanski et al.; Miller).
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) | 0.003 | 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 teacher head, 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".