Cyclic loading effects and stability assessment of trees and stumps used as anchors in cable yarding operations
Bibliographic record
Abstract
Abstract Swing yarders in running skyline configuration using either grapples or chokers represent the most common configuration for cable yarding in coastal British Columbia. In this context, whole-tree logging and short work cycles lead to heavy and repeated loads applied to the trees and stumps when used as anchors for the rigging cables. Moreover, increased harvesting of second-growth forest stands leads to the unavailability of large and safe trees, thus introducing new challenges to identify suitable anchors and potentially increases safety risks of cable yarding operations. The present study aimed to collect evidence of the mechanical response provided by anchors for typical cable yarders used in second-growth harvesting in coastal British Columbia, and test the suitability of innovative techniques for the stability assessment based on the relationship between the anchor root-plate rotations and the related applied tensile forces. A conspicuous dataset could be derived from all the surveys, storing anchor rotations from a total of 1522 work cycles of which 1224 work cycles included also tensions measurements. The methodological approach was proven effective for monitoring different rigging configurations giving proof that repeated loading affects the stability of a tree/stump which can rapidly change over few hours of active yarding operations. Acquired data proved also that comparing theoretical failure limits with anchor rotations could be a valid approach however a considerable amount of species-specific data from tree pulling tests is required.
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.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".