Sample Sufficiency for Estimation of the Mean of Rye Traits at Flowering Stage
Bibliographic record
Abstract
The objective of this study was to determine the sample size to estimate the traits mean in cultivars and sowing times, at flowering of rye culture. Ten uniformity trials were performed combining two cultivars in five sowing times. In the flowering of culture, in 100 plants of each uniformity trial, eleven traits were evaluated. The descriptive statistics was calculated and it was determined the sample size to estimate the mean in levels of precision (amplitude of the confidence interval of 95% for 5, 10, …, 35% of the mean) by resampling with replacement. The cob length presented the lowest variability among the eleven traits and, consequently, smaller sample size in both cultivars and five sowing time. There is variability in the sample size to estimate the mean among the traits, cultivars and sowing times. The measurement of 425, 276, 189 and 138 plants in cultivar BRS Progresso and 642, 413, 285 and 211 plants in cultivar Temprano, are enough to estimate the mean amplitude of the confidence interval of 95% maximum of 20, 25, 30 and 35%, respectively, for all the traits and sowing times.
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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 | 0.040 | 0.130 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".