Storage of comminuted and uncomminuted forest biomass and its effect on fuel quality
Bibliographic record
Abstract
White birch was stored in the form of bundles, wood chips, and loose slash for a period of one year to examine the changes in biomass fuel properties. The samples were collected at regular quarterly intervals to measure moisture content, CNS content, ash content, and calorific value. Data loggers were also placed into the stored woody biomass to measure the temperature change inside the piles. After the first quarter of the storage period and continuing into the next three months of storage, the moisture content showed the most significant change. The moisture content of the biomass bundles increased from 29 % to above 80 % (db). The moisture content of the pile of wood chips covered with a tarp decreased from 51% to 26% and showed a continuous decline in moisture content to the end of storage period to an average range of 16.5% (db). However, the moisture content of uncovered wood chip pile was observed to continuously increase throughout the storage period, resulting in more than double in magnitude from 59% to 160% (db). The dry matter loss was higher in wood chip piles (8~27%) than in bundles (~3%). Among the other properties, there was slightly higher loss of calorific value in wood chips (~1.6%) as compared to bundles (~0.7%) at the end of one year.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".