The impact of disc settings and slash characteristics on the Bracke three-row disc trencher’s performance
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
When reforesting, disc trenching is the most common site preparation method in Canada. The settings on today’s disc trenching units can be modified extensively, but the effect of these modifications on the work quality and machine performance is poorly understood. We studied a three-row Bracke T35.a disc trenching unit that used five different disc settings to prepare three sites with five different slash characteristics in New Brunswick. We measured the travel speed and the resulting microsite quality during 2–4 machine passes on all 25 treatment combinations, plus the fuel consumption using an engine control module during 1–3 machine passes on 15 treatment combinations. The results showed no difference in microsite quality between disc settings, but it was significantly higher with seasoned than fresh slash, parallel-aligned than perpendicular-aligned slash, and softwood than mixedwood slash. Fuel consumption was significantly lower with parallel-aligned slash and softwood slash, but it was also markedly lower with the least aggressive disc settings. Our results suggest that increased disc down pressure increases fuel consumption but does not increase microsite quality among slash, while parallel-aligned slash increases both the work- and fuel-efficiency of the disc trencher. We therefore recommend operators to use less aggressive settings when disc trenching among slash, but also to become more active in monitoring their work quality. Foresters can further increase disc trenching efficiency by prescribing the trenches parallel to slash alignment and/or in seasoned slash; however, such prescriptions must be balanced with potentially longer rotation periods and added costs to harvesting, machine relocation, and tree planting.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.000 |
| Open science | 0.001 | 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 it