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Record W2317938432 · doi:10.3130/aijs.77.521

CRACK MODEL FOR FRACTURE ENERGY TO WOOD AND FRACTURE PROCESS ZONE

2012· article· en· W2317938432 on OpenAlex
Masahiro Noguchi, Noboru Nakamura

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

VenueJournal of Structural and Construction Engineering (Transactions of AIJ) · 2012
Typearticle
Languageen
FieldEngineering
TopicWood Treatment and Properties
Canadian institutionsInnovation Cluster (Canada)
Fundersnot available
KeywordsFracture (geology)Line (geometry)Energy (signal processing)Fracture mechanicsMaterials scienceMechanicsMathematicsGeometryComposite materialStatisticsPhysics

Abstract

fetched live from OpenAlex

This paper describes the adaptability of Hillerborg fictitious crack model to timber. Using the regression line between the cumulative loss of the potential energy and the fictitious splitting length from the test data, the fracture process zone length was defined the length between the origin and x-intercept of the regression line, and the fracture energy was defined the slope of the regression line. The strength calculated by the fracture mechanical model on the specimen assuming initial splitting length equal to the fracture process zone length were agreement with the experimental results. However, the strength calculated by the fracture mechanical model using the conventional assuming initial splitting length equal to zero, was dangerously overestimated with the experimental results.

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 score0.470
Threshold uncertainty score0.547

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 communication0.0000.001
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 head0.006
GPT teacher head0.194
Teacher spread0.188 · 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