Distance Education and Computer-Based Training for the Safety Profession
Bibliographic record
Abstract
The mutualistic relationship between plants and arbuscular mycorrhizal (AM) fungi is essential for optimal plant nutrition, enabling plants to better withstand biotic and abiotic stressors and enhancing survival, reproduction, and colonization of new environments. Activities, such as soil enrichment or compaction, may decrease the benefits of AM fungi for plants, potentially reducing interactions in urban environments. Here, we examine this prediction by studying how urbanization alters AM interactions with the invasive herb Ruellia nudiflora (Acanthaceae). We collected soil and plants from deep urban sites (DUS; e.g., sidewalks), open urban sites (OUS; parks), and rural sites (RS) to analyse soil nutrient content, plant morphology, AM colonization rates, spore density, richness, and diversity. Contrary to predicted, DUS had the lowest soil nutrient concentration, except for phosphorus, reducing AM colonization. This supports the prediction of reduced AM interactions in urban environments. We also found that potassium affects the AM association. Urban plants had smaller and more compact root systems compared to their rural counterparts, but there were no discernible differences in AM fungi communities between urban and rural environments. Phosphorus enrichment in sidewalks is the main driver of reductionof R. nudiflora-AM fungi interactions in Mérida. More studies are needed to gain a better understanding of how AM fungi contribute to plant colonization in urban 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.164 | 0.028 |
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".