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Record W3026445848 · doi:10.1080/14942119.2020.1761746

Productivity and cost analysis of tower yarder systems using the Koller 507 and the Valentini 400 in southwest Germany

2020· article· en· W3026445848 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

VenueInternational Journal of Forest Engineering · 2020
Typearticle
Languageen
FieldEngineering
TopicForest Biomass Utilization and Management
Canadian institutionsSt. Peter's Hospital
Fundersnot available
KeywordsTerrainProductivityHardwoodTower craneTowerEngineeringRange (aeronautics)Agricultural engineeringSkylineLoggingForestryCivil engineeringGeographyStructural engineeringCartography

Abstract

fetched live from OpenAlex

Cable-based timber extraction offers some advantages with regard to impacts to forest stands and soils, and can be used under a wide range of conditions. It is important not only in steep terrain, but also increasingly in flat terrain when soils have low bearing capacity. In this study, utilization data from two commonly used tower yarding systems were analyzed: a tower yarder with a mounted processor (K507) and a medium-distance tower yarder (V400). Collected data included explanatory variables, such as the proportion of hardwood timber, length of skyline, direction of yarding and dimension of harvested timber. Data were analyzed with regard to the time required for machine installation including set-up and dismantling, machine productivity and resulting production costs. Possible combinations of machines and partial working steps were evaluated. Results indicated an increasing utilization of cable crane systems in horizontal yarding direction throughout the analyzed time period. Further, more time was required to process full trees when the K507 was used, although machine productivity increased. The proportion of processed timber that was hardwood significantly influenced installation times. Results demonstrated that, if the machines had above average productivity, total costs could be reduced in flat terrain by using a cable crane instead of conducting the extraction by skidders.

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)0.000
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.069
Threshold uncertainty score0.233

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.013
GPT teacher head0.226
Teacher spread0.212 · 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