Pollination biology of Impatiens capensis Meerb. in non-native range
Bibliographic record
Abstract
Pollination biology in the widespread species Impatiens capensis Meerb. has only been studied in America, specifically in zones of the U.S.A. and Canada. In this study, we investigated the pollination biology of I. capensis using an integrative identification approach using morphological and molecular tools in four populations of Northwest Poland. We also determined and compared the functional characteristics of the pollinators of the introduced species from the study sites and the native ones reported, for the latter collecting information from bibliographic sources. Visitors were identified using standard morphological keys, including identifying and classifying insect mouthparts. Molecular identification was carried out using mitochondrial DNA's cytochrome oxidase subunit I (COI). We morphologically identified 20 species of visitors constituted by 17 pollinators and three nectar robbers. DNA barcoding of 59 individuals proved the identification of 18 species (also 18 BINs). The frequency of pollinator species was primarily made up of representatives of both Hymenoptera (75%) and Diptera (21%). The morphological traits, such as the chewing and sucking mouthparts, small and big body height, and robber and pollinator behavior explained mainly the native and introduced visitors' arrangements that allow pollination success. However, to understand the process comprehensively, further investigation of other causalities in pollination success and understanding the diversity of pollinators in outer native ranges are necessary.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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".