Enhancing plant quality and outplanting growth of <i>Acacia auriculiformis</i> in dry wasteland plantations by inoculating a selected microbial consortium in the nursery
Bibliographic record
Abstract
In this study, the performance of a selected microbial consortium (Scutellospora calospora + Azotobacter chroococcum + Bacillus coagulans + Trichoderma harzianum) on Acacia auriculiformis A. Cunn. ex Benth. was evaluated through large-scale nursery trials at three locations in the Mandya district of Karnataka state, India. At each location, 500 inoculated and 500 uninoculated seedlings were cultivated. The increase in plant dry biomass of inoculated plants was 31% (mean of three locations) compared with uninoculated plants. The seedlings inoculated with microbial consortium under large-scale nursery trials were planted in wasteland at three locations, and their growth was monitored for nearly 6 years. At the end of the study, field growth of inoculated trees, measured as the biovolume index, was 52% higher than that of uninoculated trees. This study shows that the selected microbial consortium enhances nursery quality and midterm field growth of Acacia auriculiformis plantations on dry wasteland.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".