PHALARIS ARUNDINACEA A FURTHER ENERGETIC SPECIES
Bibliographic record
Abstract
Native to the temperate zones of the Northern Hemisphere, RCG is is a perennial grass widely distributed throughout Eurasia where it has different cytotypes. The species is mainly represented by an allotetraploid cytotype (2n=28), named P. arundinacea subsp arundinacea, and by a hexaploid form (2n=42), named subsp oehleri.The genetic data confirm the presence of a distinct population present throughout North America in the early twentieth century, but not present in Europe or Asia, ranging from Alaska, USA to New Brunswick, Canada. The strongest evidence to support the hypothesis that reed canarygrass is native to North America is the presence of herbarium specimens collected in the Northwest United States prior to the movement of agriculture into the region (Merigliano and Lesica 1998). Selection and breeding of reed canary grass cultivars with improved biomass yield potential offers the potential for genetic gains that can be realized across a broad agricultural landscape, due to the broad adaptation of this species and consistent genotypic expression across a wide range of sites. Phalaris arundinacea can be used as raw - material for paper pulp or as biofuel for combustion. Since it tolerates wet, poorly drained soils, it has generally been used for grass waterways. More recently, it has been used as a hay crop under wastewater irrigation systems using treatment effluent. Reed canarygrass is unusual in that it also has excellent drought tolerance and is an outstanding competitor and yielder under high nitrogen (N) conditions. Production of renewable energy from herbaceous crops on agricultural land is of great interest since fossil fuels need to be replaced with sustainable energy sources. Reed canary grass (RCG), Phalaris arundinacea L. is an interesting species for this purpose.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
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".