Weeds and ground beetles (Coleoptera: Carabidae) as influenced by crop rotation type and crop input management
Bibliographic record
Abstract
Weeds and ground beetles are bioindicators of cropping system sustainability. In 1992, a study was initiated near Winnipeg to determine how cropping system diversity and input use affect populations of weeds and ground beetles, and the association between weed and ground beetle populations. Three, four-year rotations (rotation 1 = annual crops only; rotation 2 = annuals plus one green manure crop; rotation 3 = annuals plus two year alfalfa hay crop) were subdivided into four subplots based on fertilizer (f) and herbicide (h) use (all four combinations: f+h+, f+h-, f-h+, f-h- in each rotation type). A prairie grass system was included in each of three replicates. A common test crop (flax ['Linum usitatissimum' L.]) was seeded in all plots at the end of each rotation cycle (1995; 1999). Plant growth, crop yield, weed and ground beetle diversity weed populations and ground beetle activity, were assessed each year and subjected to univariate analysis. Weed populations and ground beetle activity for 1995 to 1999 were analyzed using multivariate redundancy analysis (RDA). (Abstract shortened by UMI.)
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 | 0.000 | 0.001 |
| 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) | 0.001 | 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".