Physiological Maturity of Parapiptadenia rigida Seeds
Bibliographic record
Abstract
The establishment of appropriate standards related to the physiological and morphological aspects of the seeds are fundamental procedures to help the nurserymen and seed producers in determining the maturity and the appropriate moment of collection of the fruits. In this sense, the objective of this research is to evaluate the physiological maturation of seeds of Parapiptadenia rigida by means of germination and vigor tests, based on the color of the pods. The seeds were collected in June 2017, from three matrices located in the municipality of Marechal Cândido Rondon, Paraná, Brazil. The pods were classified in four stages of maturation, according to the Chart of colors model “Munsell colors chart” for plants tissues, and measured the biometric parameters. The parameters observed to evaluate the germinative potential are: first germination count, germination velocity index, emergency velocity index, and fresh and dry matter masses of seedlings. The experimental design was completely randomized, with five maturation stages and four replicates of 25 seeds each. The averages were compared using the Tukey test at a 5% probability. The germination test showed that the increase in physiological potential of P. rigida seeds is associated with the progresses of pod maturation. Therefore, the vigor test demonstrated that the physiological maturation of the species is simultaneous with the change of coloration and maturation of the pods.
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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 | 0.000 |
| 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) | 0.001 | 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".