Determining the emergence timing, morphological characteristics, and species composition of Galium populations in western Canada
Bibliographic record
Abstract
Three species of Galium are commonly believed to thrive in western Canada; Galium aparine L., Galium spurium L. and Galium boreale L. Prairie weed surveys indicate that ‘cleavers’ (Galium aparine and Galium spurium) have increased in relative abundance since the 1970’s, resulting in contaminated canola seed and harvest difficulties. The ability to identify and distinguish between species is important to understand their competitive ability or potential to outcross, potentially spreading traits such as herbicide resistance between species. The objectives of this thesis were to: (1) identify variation in the ITS1-5.8S-ITS2 that could be used for species identification, (2) verify the species composition of Galium populations in western Canada, and (3) evaluate emergence timing in spring and fall and morphological traits impacting cleavers biology. The target ITS1-5.8S-ITS2 complex was isolated from the ribosomal DNA of ten cleavers populations (including reference Galium aparine and Galium spurium populations), and was then cloned and sequenced to identify single nucleotide polymorphisms that could be used to differentiate species. The results identified a sequence variation that consistently differentiates between Galium species. In addition to several variable nucleotides in the ITS regions, one variable loci was identified within the highly conserved 5.8S gene. Sequence analysis of the ITS1-5.8S-ITS2 complex of Galium field collections from western Canada indicated that all samples were G. spurium. To address objectives 2 and 3, a common garden experiment of six cleavers populations with different geographical origins in western Canada were planted and their emergence monitored for a two-week period. Various other traits were also measured for each population. Field emergence studies showed differences between populations with regard to start of emergence (~150-250 GDD) and time to 50% emergence (~275-470 GDD) in spring. Fall emergence among populations was very low (1-9%) in comparison to spring emergence (2-17%). Plant traits measured in the study did not differ between populations, supporting the results of the molecular work and leading to the conclusion that all populations were derived from a single species.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".