Phenology of <i>Psychotria tenuinervis</i> (Rubiaceae) in Atlantic forest fragments: fragment and habitat scales
Bibliographic record
Abstract
The objective of this study was to investigate (1) whether the reproductive phenology of Psychotria tenuinervis Muell. Arg. is influenced by climatic conditions (precipitation and temperature); (2) whether there are differences in the reproductive phenology of P. tenuinervis between fragments (fragment scale); and (3) whether there are differences in the reproductive phenology of P. tenuinervis among anthropogenic edges, natural edges, and in the forest interior within a fragment (habitat scale). The patterns of flowering and fruiting found in 2002 and 2003 were similar between forest fragments, and proximate factors were not very important in determining the reproductive phenology of P. tenuinervis. There was phenological similarity among the three habitats on a habitat scale, probably because of the extensive heterogeneity within each habitat, with the percentage of flowering and fruiting individuals and the intensity and duration of these phenophases varying among the sample plots. This high variability within habitats indicated that factors other than the distance from the edges (i.e., gaps, matrix composition, and edge age) probably had a greater influence on the reproductive phenology of P. tenuinervis. These results also indicate that heterogeneity within fragmented habitats needs to be considered in conservation and management programs for fragmented landscapes.
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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 | 0.001 | 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".