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Calibration of Resistance Factor for Self-Tapping Screws in Canada

2022· article· en· W4205220474 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Structural Engineering · 2022
Typearticle
Languageen
FieldDecision Sciences
TopicProbabilistic and Robust Engineering Design
Canadian institutionsNatural Sciences and Engineering Research Council of CanadaUniversity of Alberta
Fundersnot available
KeywordsTappingReliability (semiconductor)Reliability engineeringResistance FactorsCalibrationConsistency (knowledge bases)Resistance (ecology)Computer scienceStructural engineeringEngineeringStatisticsMathematicsMechanical engineering

Abstract

fetched live from OpenAlex

Under the load and resistance factor design philosophy used in North America, building codes structures are designed using load and resistance factors calibrated to a target reliability level. Despite this, few attempts have been made to calibrate resistance factors for timber connections. A calibration process was carried out for the withdrawal resistance of axially loaded self-tapping screws using a database of test results from across Canada. Two load cases were considered, reflecting load combinations and statistics drawn from the 2015 National Building Code of Canada and from a proposal developed to provide greater consistency in reliability outcomes, and the reliability under each case was determined using the first-order reliability method (FORM). Given the low ductility–brittle nature of withdrawal failures, a resistance factor of φ=0.7 was recommended for a target reliability index of β=4.0. The outcomes will assist in the selection of a resistance factor for self-tapping screws for use in the Canadian timber design standard, CSA O86.

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)0.001
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 score0.147
Threshold uncertainty score0.437

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.035
GPT teacher head0.263
Teacher spread0.227 · 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