Influence of annual fluctuations in environmental conditions on chasmogamous flower production in Viola striata<sup>1</sup>
Bibliographic record
Abstract
Cortés-Palomec, A. and H. E. Ballard (Department of Environmental and Plant Biology, Ohio University, Athens, Ohio, 45701). Influence of annual fluctuations in environmental conditions on chasmogamous flower production in Viola striata. J. Torrey Bot. Soc. 133(2): 312–320. 2006.—The ecological factors affecting chasmogamous flower production by Viola striata, a perennial herb widely distributed in temperate forests of the northern and eastern United States and southern Canada, were studied in a natural setting. Forty semi-permanent quadrats were established at two sites in southern Ohio where populations of V. striata are abundant. Investigations were conducted from April to mid-June in 2002 and 2003. The number of chasmogamous flowers produced per individual per quadrat was recorded and the percentage of flowers becoming fruits per plant was measured as an indication of reproductive success. For each quadrat, canopy openness and soil properties (N, K, P, Ca, Mg, pH, and moisture) were documented and their effects on chasmogamous flower production were evaluated. Chasmogamous flower production was correlated in some, but not in all cases with light availability one to two weeks before the population reached the peak of blooming. Multiple correlations showed that phosphorus and calcium were important in all significant cases while light, magnesium, nitrogen and pH were important in some cases. Chasmogamous flower success was highly variable ranging from 1 to 100 % of success in fruit set possibly due to differential pollinator activity.
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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".