A Comparative Study of Total and Leachable Concentrations of Metallic Micronutrients in Canadian Marginal and Agricultural Land used for Sorghum Production
Bibliographic record
Abstract
Marginal lands have not been well studied. As part of a five-year project to develop low-cost and high production systems for growing sorghum biomass on marginal lands in Canada, this research focuses on analyzing the total and leachable concentrations of metallic micronutrients (Cu, Fe, Mn, Mo, and Ni) in soil samples collected from one agricultural (London) and two marginal sites (Ottawa and Simcoe) in Ontario. This thesis aims to understand the differences for the metallic micronutrients within marginal and fields and if the sorghum and N-fertilizer alters their leachability. The concentrations were determined using acid digestion (total) and synthetic precipitation leaching procedure (leachable). The results concluded that there were no consistent trends between the various hybrids and the application of N-fertilizer (Urea). The elements Mn and Fe demonstrated a moderately negative association between the leachable concentration and the fresh biomass of the sorghum. The altering of the soil moisture (oven-dried and field-moist) demonstrated that the dry soil had higher leaching concentrations than the moist soil. The first-year results indicated a potential influence of metallic micronutrients within the soil and sorghum growth.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 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".