The effects of soil fumigation on pine seedling production, weeds, foliar and soil nutrients, and soilborne microorganisms at a south Georgia (U.S.A.) forest tree nursery
Bibliographic record
Abstract
Pine seedling production and pest problems were evaluated in plots fumigated with methyl bromide and nonfumigated plots over a 6-year period at a Georgia nursery. Fumigation increased bed densities for loblolly pine (Pinus taeda L.) in 1996 and slash pine (Pinus elliottii Engelm. var. elliottii) in 1998; differences were not observed between treatments in other years. The root collar diameter, height, and root and shoot masses of loblolly pine seedlings were often greater in fumigated plots during the first 3 years. Morphological characteristics rarely differed between treatments for slash pine. The primary pest problem was nutsedge (Cyperus spp.); most other weeds were controlled with herbicides used operationally at the nursery. Plant-parasitic nematode populations did not increase over time and were not a problem. Although Fusarium and Pythium spp. were more common in soil and on roots in nonfumigated plots, evidence of disease was rare. Fumigation increased the abundance of and changed the composition of Trichoderma spp. in soil and on roots. Soil manganese and iron, and foliar manganese, phosphorus, and nitrogen were greater in the fumigation treatment in some years. A better understanding of the risks of soilborne diseases may facilitate the development of pest management programs that are more cost-effective.
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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) | 0.001 | 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".