Reference values for germination and emergence measurements
Bibliographic record
Abstract
Why should we care about reference values for germination and emergence measurements? Because they can help in the conservation of species and thus the recovery or restoration of altered areas. Therefore, for the first time, we evaluated the germination and emergence processes of diaspores of five Cerrado species to propose reference values for the germination and emergence measurements to enable species comparison, and consequently, facilitate better conservation decisions. The five species have diaspores with high physiological quality and intraspecific variability in relation to most of the germination and emergence measurements, showing that they still retain their reproductive potential. The processes of seed germination and seedling emergence in Anadenanthera colubrina (Vell.) Brenan and Ceiba speciosa (A.St.-Hil.) Ravenna and seedling emergence in Astronium urundeuva Engl. were faster and more synchronised than those of Cedrela fissilis Vell. (emergence) and Lithraea molleoides (Vell.) Engl. (germination and emergence), indicating the presence of dormancy in the diaspores of the last two species. However, considering the reference values determined here, all the species could be considered very slow and very asynchronous. This means that all the species use large environmental windows to establish themselves, where the spreading of seed germination and seedling emergence over time is an important survival advantage.
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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 | 0.014 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.003 |
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".