{"id":"W4386035087","doi":"10.1016/j.engfailanal.2023.107562","title":"Fatigue characterization of wire arc additive manufactured AWS ER100S-G steel: fully reversed condition","year":2023,"lang":"en","type":"article","venue":"Engineering Failure Analysis","topic":"Additive Manufacturing Materials and Processes","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of New Brunswick","funders":"Engineer Research and Development Center","keywords":"Arc (geometry); Materials science; Characterization (materials science); Metallurgy; Composite material; Structural engineering; Engineering; Mechanical engineering; Nanotechnology","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":[0.0003236589,0.0004217204,0.0003558621,0.0006670277,0.0003166723,0.0002014635,0.000608153,0.0008346973,0.003263923],"category_scores_gemma":[0.0003912708,0.0002248923,0.0002932076,0.0003591692,0.0003012539,0.0002945247,0.000141694,0.000258322,0.0006855727],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002386277,"about_ca_system_score_gemma":0.0002789334,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002597047,"about_ca_topic_score_gemma":0.006050638,"domain_scores_codex":[0.9995801,0.00002169786,0.00002654786,0.00008939683,0.0002312512,0.00005094198],"domain_scores_gemma":[0.9994405,0.00006554752,0.00006481996,0.00005157627,0.0003511932,0.0000262969],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003891983,0.00003868772,0.00196593,0.0001078016,0.00001212184,0.0001614154,0.0002192145,0.001435919,0.9871082,0.00008532326,0.0004651886,0.008011051],"study_design_scores_gemma":[0.00002774651,0.002067087,0.09354807,0.00003099542,0.00005914499,0.000514662,0.000336314,0.02085513,0.8778892,0.00008171362,0.004535922,0.00005408089],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9919491,0.0001814153,0.005095589,0.00003090857,0.00001780513,0.00002588342,0.0006838311,0.0002166564,0.001798638],"genre_scores_gemma":[0.9945274,0.00005857262,0.001909369,0.00001765304,0.000004141433,0.00002125478,0.0006219792,0.00003376893,0.002805927],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003263923,"threshold_uncertainty_score":0.01091892,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007600887872551258,"score_gpt":0.2048373573674562,"score_spread":0.1972364694949049,"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."}}