{"id":"W2121907181","doi":"10.1139/l06-058","title":"Analytical approach for shear lag in welded tension members","year":2006,"lang":"en","type":"article","venue":"Canadian Journal of Civil Engineering","topic":"Structural Load-Bearing Analysis","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Welding; Truss; Structural engineering; Shear (geology); Tension (geology); Lag; Bracing; Engineering; Materials science; Ultimate tensile strength; Composite material; Computer science","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002228521,0.000166296,0.0003296607,0.0007595103,0.00003106372,0.00004911872,0.0001687582,0.0001046816,0.00004873077],"category_scores_gemma":[0.0001020072,0.0001692009,0.0001623863,0.0004218348,0.00001805786,0.0001280147,0.000004486733,0.000296851,0.000001170125],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003386112,"about_ca_system_score_gemma":0.00008758909,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00183414,"about_ca_topic_score_gemma":0.02799286,"domain_scores_codex":[0.9989023,0.000007344073,0.0004166736,0.000109778,0.00013889,0.0004249964],"domain_scores_gemma":[0.9993918,0.00005329336,0.00003883923,0.0001290004,0.00007271865,0.0003143677],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000002671949,0.000001990126,0.001481215,0.0000541894,0.00004593449,0.00004391913,0.00003999828,0.9940662,0.00230972,0.0002576704,0.001596454,0.0001000099],"study_design_scores_gemma":[0.0004571666,0.0000217439,0.008422763,0.0000782617,0.00006189274,0.0001055684,0.00004191283,0.9857076,0.001211221,0.00008201921,0.003559143,0.0002506801],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8928264,0.002799351,0.08990864,0.000248267,0.001345283,0.0003515508,0.000029653,0.0001697822,0.0123211],"genre_scores_gemma":[0.9948449,0.00000472145,0.004788719,0.000009718279,0.0002523353,0.00000274125,0.000006303443,0.00004345265,0.00004713803],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1020185,"threshold_uncertainty_score":0.9897437,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007657719679920989,"score_gpt":0.1818073459725977,"score_spread":0.1741496262926767,"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."}}