Effects of Organic Farming and Agricultural Landscape Composition on Relative Bat Diversity and Abundance
Bibliographic record
Abstract
Some ways that agricultural areas have intensified, include increased agro-chemical inputs, use of annual row crops and agricultural extent.These changes would be expected to reduce insect prey for bats, causing smaller bat populations to be supported.Chapter 1 examines the influence that the proportion of the landscape in agriculture and the proportion of agricultural lands in annual crops (vs.perennial forage crops) has on relative bat abundance and diversity.We found that bat abundance was highest in landscapes that had a low proportion of agriculture and where the proportion of agriculture in annual crops was about equal to the proportion in perennial forage.Chapter 2 examines the influence of organic versus conventional farming practices using matchorganic conventional soybean field pairs on bat diversity, bat abundance and bat prey abundance.We found organic fields had higher bat diversity, bat abundance and bat prey abundance than conventional fields.Chapter 2: Higher bat abundance and bat food abundance at organic than conventional soybean fields .......
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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 | 0.000 | 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) | 0.004 | 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".