Purpose-grown biomass crops in Nova Scotia : statistical predictive modeling and real-world verification
Bibliographic record
Abstract
The bioeconomy of Nova Scotia could be stimulated by the increased production of purpose-grown biomass crops grown on marginal agricultural lands.Biomass yields of four crops of interest (switchgrass, miscanthus (Miscanthus × giganteus L.), coppiced hybrid-poplar and willow) were predicted using linear mixed-effects models created from published data in areas with similar climates to Nova Scotia.These models were validated and refined using yields from five field sites established across the province.Two locally sourced, low-cost soil amendments (pulp and paper mill effluent residue and liquid anaerobic digestate) and one plant biostimulant (Ascophyllum nodosum extract) were applied to the crops during the establishment year to evaluate effects on crop establishment and early yield.This research focuses on two of the five aforementioned local field sites, Bible Hill and Nappan.The grasses were harvested annually, while the trees were harvested after one 3-year growth cycle post-coppicing.Mean miscanthus biomass yield three years post-establishment (Year 4) across two sites was 7,200 kg ha -1 year -1 , while switchgrass yield was 1,800 kg ha -1 year -1 .The mean predicted yields across field sites, based on the developed models, were 6,700 kg ha -1 year -1 and 4,000 kg ha -1 year -1 for miscanthus and switchgrass, respectively.Mean hybrid-poplar and willow biomass yields across sites after one growth cycle were 1,200 kg ha -1 year -1 and 1,700 kg ha -1 year -1 , respectively, while yield models predicted biomass yields of hybrid-poplar (3,300 kg ha -1 year -1 ) and willow (4,900 kg ha -1 year -1 ) across Bible Hill and Nappan field sites.Biomass yields reported in the field are likely lower than predicted due to the infancy of the field trials; these crops have likely not reached their maximum yield potential yet.Minimal differences were reported between amendment treatments and management factors during establishment have also been identified as important influences on early yields of these crops.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".