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Record W3162809187 · doi:10.5552/crojfe.2021.886

The Effect of Yarding Technique on Yarding Productivity and Cost

2021· article· en· W3162809187 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCroatian journal of forest engineering · 2021
Typearticle
Languageen
FieldEngineering
TopicForest Biomass Utilization and Management
Canadian institutionsUniversité Laval
FundersEuropean Commission
KeywordsProductivityDeflection (physics)Tree (set theory)EngineeringTerrainAgricultural engineeringTransport engineeringMathematicsGeographyCartographyEconomics

Abstract

fetched live from OpenAlex

Cable yarding is a well establish technology for the extraction of timber in steep terrain. However, it is encumbered with relatively low productivity and high costs, and as such this technology needs to adapt and progress to remain viable. The development of biomass as a valuable byproduct, and the availability of processors to support yarder operations, lend themselves to increasing the level of whole-tree extraction. Double-hitch carriages have been developed to allow for full suspension of whole-tree and tree-length material. This study compared a standard single-hitch to a double-hitch carriage under controlled conditions, namely in the same location using the same yarder with downhill extraction. As expected, the double-hitch carriage took longer to load up (+14%), but was able to achieve similar productivity (10–11 m3 per productive machine hour) through increased inhaul speed (+15%). The importance of this study is that it demonstrates both the physical and economic feasibility of moving to whole-tree extraction using the double-hitch type carriage for longer corridors, for settings with limited deflection, or areas with lower tolerance for soil disturbance.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.824
Threshold uncertainty score0.393

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.004
GPT teacher head0.198
Teacher spread0.193 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it