Sample size in studies on the germination process
Bibliographic record
Abstract
Studies on diaspore germination in native species with low economic relevance but great ecological significance have been based on a wide range of sample sizes. However, can the sample size change the physiological inferences made from germination measurements? To answer this question, diaspores of six Cerrado species were evaluated for germinability, germination time (initial, mean, and final), germination velocity (mean germination rate and Maguire’s rate), coefficient of variation of the germination time, and synchronization index of the germination process. Germinability, final time, mean time, and synchronization index were robust with respect to sample size fluctuation. Maguire’s rate, initial time, coefficient of variation of the germination time, and mean germination rate, in contrast, were affected by sample size fluctuation, at least in one of the species tested. The robustness of the time measurements and the synchronization index also demonstrates that the germination process occurs in a cadenced rhythm, much like a biological clock. Among the measurements evaluated, Maguire’s rate is the only one that must be avoided, since it is strongly influenced by sample size and by the balance between germinability and mean germination rate. These results demonstrate that sample size can affect inferences about the germination process and can compromise restoration and (or) conservation efforts.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.175 | 0.379 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".