Analysis of genetic similarities among species of <i>Fragaria</i>, <i>Potentilla</i>, and <i>Duchesnea</i> found in northwest Argentina by using morphological, anatomical, and molecular characters
Bibliographic record
Abstract
Morphological, anatomical, and molecular techniques were used to characterize wild strawberry and wild strawberry-like species in northwest Argentina. Characteristics of leaves, flowers, runners, achenes, and genomic DNA polymorphisms were used to analyze similarities among Potentilla tucumanensis Castagnaro & Arias, Duchesnea indica (Andr.) Focke, and Fragaria vesca L. Comparison of phenograms obtained by using morphological and anatomical traits or genomic DNA characters revealed similar clustering of the species. Both phenograms suggest that D. indica is more closely related to P. tucumanensis than to F. vesca. Using the randomly amplified polymorphic DNA (RAPD) technique with specific primers, we detected polymorphic bands that permit the identification of P. tucumanensis, D. indica, and F. vesca. In addition, we report new morphological and anatomical characters that can be used as diagnostic traits for better identification of species in reproductive and vegetative states.Key words: Fragaria, Potentilla, Duchesnea, RAPD, DNA fingerprinting, morphological traits, anatomical traits.
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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".