{"id":"W2172757778","doi":"10.1109/tim.2003.822474","title":"Implementation of a Mechanics-Based System for Estimating the Strength of Timber","year":2004,"lang":"en","type":"article","venue":"IEEE Transactions on Instrumentation and Measurement","topic":"Wood Treatment and Properties","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Finite element method; Stress (linguistics); Structural engineering; Grading (engineering); Feature (linguistics); Correlation coefficient; Size effect on structural strength; Nondestructive testing; Engineering; Strength of materials; Compressive strength; Computer science; Materials science; Machine learning; Composite material; Physics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004927433,0.0005938182,0.000421383,0.0007355564,0.0003801896,0.0006029379,0.001075648,0.0004768758,0.005132195],"category_scores_gemma":[0.001560223,0.0002895968,0.0001577344,0.0004686217,0.0002435547,0.0006949466,0.0003445977,0.0004190127,0.001870276],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003721554,"about_ca_system_score_gemma":0.0008078622,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002078527,"about_ca_topic_score_gemma":0.002655035,"domain_scores_codex":[0.9996802,0.00003406173,0.00002503572,0.0001017999,0.0001370796,0.00002188233],"domain_scores_gemma":[0.9993864,0.0001436288,0.00005920264,0.0001072122,0.0002679971,0.00003548304],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003428456,0.0002913031,0.01417534,0.0001463563,0.00006612096,0.000159828,0.0001889213,0.01578001,0.2804847,0.004214146,0.004816023,0.6793343],"study_design_scores_gemma":[0.00009995866,0.0009910277,0.02230981,0.00004005027,0.0001049044,0.0005945378,0.00007882617,0.5845855,0.3605741,0.002588824,0.02794963,0.00008278041],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04703802,0.00005968176,0.9327136,0.00006755449,0.0000609485,0.000423111,0.0002211497,0.01612003,0.003295803],"genre_scores_gemma":[0.3020249,0.00007447446,0.6918586,0.00009026427,0.00004064861,0.0004344229,0.0004852664,0.0002370834,0.004754299],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005132195,"threshold_uncertainty_score":0.01716894,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03440896871916346,"score_gpt":0.2491648327450403,"score_spread":0.2147558640258769,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}