Influence of Weather on the Predicted Moisture Content of Field Chopped EnergySorghum and Switchgrass
Bibliographic record
Abstract
Abstract. To determine the effects of weather on harvested moisture content (MC) of switchgrass (Panicum virgatum) and energy sorghum (Sorghum bicolor), tracking of harvest progress on individual fields in the Integrated Biomass Supply and Logistics (IBSAL) model was modified to allow: i) rewetting of swathed material in the drying formulae; and ii) field queuing rules based on equipment availability and weather. Estimated crop yield and initial MC by harvest date, as observed in field trials, along with the modeling of different delays between mowing and harvest allowed estimation of harvested MC, annual tonnage processed and associated processing cost differences by crop and location over 10 years. Extending the hours of annual equipment use had minor implications on cost of production. Energy sorghum proved difficult to dry in the field. Its higher yield, leading to shorter supply distance to the plant, may justify harvesting of energy sorghum early in the season with drier weather. Later harvest for lower-yielding switchgrass offers MC advantages.
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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 | 0.000 | 0.000 |
| 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) | 0.001 | 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".