An evaluation of biochar pre-conditioned with urea ammonium nitrate on maize (Zea mays L.) production and soil biochemical characteristics
Why this work is in the frame
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Bibliographic record
Abstract
Dil, M., Oelbermann, M. and Xue, W. 2014. An evaluation of biochar pre-conditioned with urea ammonium nitrate on maize (Zea mays L.) production and soil biochemical characteristics. Can. J. Soil Sci. 94: 551-562. Biochar can enhance soil fertility, plant nutrient uptake and crop production. Using a potted study, we quantified the effects of adding biochar at 1 t ha-1 (Char), biochar pre-conditioned with urea ammonium nitrate [UAN (Char+)], or UAN only to a control (Contr) with no amendments on maize (Zea mays L.) biomass production, tissue carbon (C) and nitrogen (N) concentrations, N uptake (NU), N utilization efficiency (NUtE), and soil chemistry and biology in coarse-, medium- and fine-textured soils over 6 wk. Soil pH decreased (P<0.05) in Char+ and UAN treatments for all soil textures. Soil organic carbon (SOC) increased (P<0.05) in the coarse and medium textured soil in Char and Char+ treatments. Soil ammonium and soil nitrate were different (P<0.05) among treatments; increasing or decreasing depending upon soil texture. Soil microbial biomass C was lowest (P<0.05) in the UAN treatment for all soil textures. Soil potential microbial activity was significantly greater in the coarse-textured soil in only the Char and Char+ treatments. Maize biomass, tissue N concentration, and NU increased (P<0.05) in soils amended with Char+ or UAN only. NUtE was lower (P<0.05) in Char+ and UAN treatments in the coarse- and medium-textured soils, but this was reversed for the fine-textured soil.
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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 | 0.001 | 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) | 0.000 | 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 it