Effect of environmental characteristics on<i>Pythium</i>and<i>Mesocriconema</i>spp. in golf course greens in Alabama
Bibliographic record
Abstract
The role the environment has on populations of Pythium and Mesocriconema spp. was investigated at 5 golf course locations in east central Alabama. Every 4 to 5 weeks soil samples were collected from 3 golf greens on each of the 5 golf courses. Environmental data, including air and soil temperature, pH and relative humidity, were also collected. Dilution plating and a combined sieving and sugar flotation procedure were conducted to determine the populations of Pythium and Mesocriconema spp. for each month. Isolates of Pythium from 4 months were also identified. Pythium spp. populations increased as soil temperature and ambient air temperature prior to sampling decreased (P < 0.05). Pythium spp. populations were highest in the winter and lowest in the spring. At some locations, populations of Mesocriconema spp. increased as soil acidity and populations of Pythium spp. decreased (P < 0.05) and as ambient air temperature prior to sampling increased (P < 0.05). Eight species of Pythium were isolated from 4 months, with Pythium rostratum being the most commonly isolated. Results suggest that Pythium and Mesocriconema spp. prefer different soil environments.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".