Evaluation of <i>Galium</i> species and populations using morphological characters and molecular markers
Bibliographic record
Abstract
Summary Three Galium species are believed to be present across western Canada: Galium aparine, Galium spurium and Galium boreale. Galium spurium and G. aparine are very difficult to distinguish morphologically, which is problematic for crop consultants and weed surveyors, and could have implications for control measures. Molecular techniques could potentially make identification easier and more rapid than using chromosome counts, as is currently done. The objective of this study was to identify morphological traits and/or genetic polymorphisms capable of species differentiation. To this end, Galium seed of unknown speciation were collected from nine field populations across western Canada and, along with two reference samples of G. spurium and G. aparine, were characterised for both morphological traits and their ribosomal ITS1‐5.8S‐ITS2 genomic sequence. In addition, single nucleotide polymorphism variation within the highly conserved 5.8S ribosomal RNA gene was identified that could consistently differentiate Galium species. Sequence analysis of the ITS1‐5.8S‐ITS2 region of field collections from western Canada indicated that all samples were G. spurium and all were highly related to each other. These results were supported by a distinct lack of variation in morphological traits, as nearly all plant traits measured did not differ between populations. This suggests that all sampled populations, and perhaps most of the Galium populations across western Canada, are derived from a single species, G. spurium.
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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 | 0.001 | 0.000 |
| Open science | 0.001 | 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".