Path Analysis of Green Maize Components from Hybrids Cultivated Under Reduced Spacing
Bibliographic record
Abstract
The yield and cause and effect relationships of green-ear production components of hybrids cultivated in reduced spaced environments were investigated aiming to increase the green ear harvest, as well as to identify the main characteristics that contribute most to the productivity. Four row spacings were evaluated using three commercial hybrids. The experiment lasted three months and were evaluated: plant height (PH) and ear insertion height (EIH), leaf area (LA), stem diameter (SD), total number of ears, total ear yield, number of ear with straw and without straw, yield of ears with straw (YES) and yield ear without straw (YEWS), ear length (EL) and ear diameter (ED). In addition, the full correlation in direct and indirect effects was performed by the path analysis of the PH, EIH, LA, SD, EL, ED characters on the YEWS. It was found that the reduction of spacing to 60 cm favors higher YEWS without compromising the quality, size and diameter of the green ears. However, the EL, EIH and SD are the main characters that directly and indirectly influence the yield of green ears of maize hybrids cultivated in reduced spaced environment.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".