Influence of pipelines and environmental factors on the endangered plant, <i>Halimolobos virgata</i> (Nutt.) O.E. Schultz over a 10 year period
Bibliographic record
Abstract
We investigated the effects of pipeline construction and environmental factors on the occurrence and characteristics of the endangered plant Halimolobos virgata (Nutt.) O.E. Schultz. The plants were surveyed from 2007 to 2016 at three sites along the Keystone Pipeline in southern Alberta, Canada. Plant height, number of flowers and siliques, as well as microhabitat and climate data were collected up to 300 m away from the pipeline. Pipeline construction and distance had no effect on plant numbers or physical characteristics, with occurrences increasing markedly over time. Greater litter cover and depth and spring precipitation were associated with plant height and number of flowers and siliques. Vegetation cover was negatively correlated with H. virgata cover; however, plant height and number of flowers and seed pods were positively influenced by graminoid cover. The highest occurrences of H. virgata coincided with the driest and wettest years, and higher winter and spring temperatures. Some of this pattern can be attributed to the plant’s annual, biennial, and short perennial life forms, which may overlap and create a temporary exponential growth rate for an annual plant under ideal conditions. This research highlights the importance of understanding a species’ life history for the development of effective conservation and recovery strategies.
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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 | 0.000 | 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) | 0.000 | 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".