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UTILIZATION OF PEELER CORES FOR PRODUCING BEAMS WITH HOLLOW CROSS - SECTION

2022· article· en· W4390597010 on OpenAlexaff
Daniel Koynov, Miglena Valyova

Bibliographic record

VenueDrewno Prace Naukowe Doniesienia Komunikaty = Wood Research Papers Reports Announcements · 2022
Typearticle
Languageen
FieldEngineering
TopicMetallurgy and Material Forming
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsSection (typography)Cross section (physics)Materials scienceForensic engineeringComposite materialPolymer scienceEngineeringComputer sciencePhysics

Abstract

fetched live from OpenAlex

This study presents an opportunity to utilize peeler cores derived from poplar wood for the production of hollow beams.In this way, final products to meet the needs of consumers can be obtained.The proposed novel methods for sawing and gluing the produced materials allow rational application of the waste raw material in the plywood manufacturing.Another advantage in this case is that products with a square cross-section with dimensions close to or corresponding to the standard ones are obtained from small-diameter round wood.The raw material used to receive the proposed hollow beams is up to 33% less than a conventional beam with the same dimensions.The manufactured products are lighter and with a significantly stable cross-sectional shape, compared to natural wood beams with the same dimensions.Sawing the peeler cores and obtaining materials with a triangular and trapezoidal cross-section helps to achieve volume yields from 60.6% to 71.1% of the raw material initial volume.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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)0.0010.001

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 head0.056
GPT teacher head0.332
Teacher spread0.276 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueDrewno Prace Naukowe Doniesienia Komunikaty = Wood Research Papers Reports AnnouncementsSame topicMetallurgy and Material FormingFrench-language works237,207