Effect of Potassium Fertilizer Application on Elymus nutans Seed Yield in Tibet
Bibliographic record
Abstract
Elymus nutans is extensively cultivated in Tibet,its seed production is very important in the local livestock production.Field experiments were conducted in Dazi Station in 2009.The results showed that K fertilizer application at different stages could affect fertile tillers/m2,spikelets/fertile tiller,florets/spikelet,seed number/spikelet and thousand-seed weight of Elymus nutans,K fertilizer application increased the actual seed yield.The actual seed production of Jointing stage was 221.8kg/hm2,and it was significantly different from ck at 0.05 level.The potential and manifestation seed yield in tillering stage were the highest for 2803.8kg/hm2 and 1040.2kg/hm2,and were significantly different from ck at 0.01 level.
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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 | 0.000 | 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) | 0.000 | 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".