Bibliographic record
Abstract
A field experiment was organized on sandy soil (TypicTorriorthent) at a private vine yard (Agrofarms) at South El-Tahrer Province, El-Behiera Governorate, Egypt during 2015/2016, to establish the adequate ranges for some nutrients (N, P, K, Ca, Mg and Cl) through DRIS method under different Kfertilizers combination ratios.Fertigation was applied at the following twelve mixing ratios of potassium chloride (60 % K2O) K-KCl, potassium nitrate (46 % K2O) K-KNO3 and potassium sulfate (50 % K2O) K-K2SO4: (100 / 0 / 0), (75 / 25 / 0), (50 / 50 / 0), (25 / 75 / 0), (0 / 100 / 0), (0 / 75 / 25), (0 / 50 / 50), (0 / 25 / 75), (0 / 0 / 100), (25 / 0 / 75), (50 / 0 / 50) and (75 / 0 / 25) relative to 100 that equal to the total K requirement during growth stage (160 unit).The results showed that the lowest Nutrient Balance Index (NBI) was listed from blending treatments 0 % KCl + 50 % KNO3 + 50 % K2SO4, 25 % KCl + 75 % KNO3 + 0 % K2SO4, 0 % KCl + 25 % KNO3 + 75 % K2SO4 and 50 % KCl + 50 % KNO3 + 0 % K2SO4 were attained 25.90, 30.23, 30.56 and 33.13, respectively; these treatments achieved high quantity of grape yield which were 12.5, 11.0, 9.66 and 9.54 ton fed-1, respectively.The sufficient ranges for N, P, K, Ca, Mg and Cl were 0.97 to 0.86, 0.27 to 0.20, 2.81 to 2.11, 2.81 to 2.11, 1.05 to 0.77, 0.69 to 0.53 and 0.66 to 0.34 %, respectively.Whereas the deficient values of N, P, K, Ca, Mg and Cl when the concentration of these nutrients are less than 0.80, 0.16, 1.75, 0.64, 0.45 and 0.19 %, respectively.
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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) | 1.000 | 0.996 |
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; both teacher heads agree on what is shown here.
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".