{"id":"W4366506757","doi":"10.11159/icsect23.135","title":"Innovative Training Methodology, In Occupational Risk Prevention, For Welding Tasks in Metal Structures","year":2023,"lang":"en","type":"article","venue":"Proceedings of the World Congress on Civil, Structural, and Environmental Engineering","topic":"Engineering and Environmental Studies","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Training (meteorology); Welding; Computer science; Engineering; Mechanical engineering","routes":{"ca_aff":false,"ca_fund":false,"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":[0.0002813826,0.0002746607,0.0003344588,0.0003643039,0.00008378285,0.00001902228,0.0001743732,0.00006908862,0.00001028208],"category_scores_gemma":[0.00008387465,0.0002386419,0.00006824164,0.0005080793,0.00009111341,0.0001679136,0.0001053304,0.0003080426,5.271801e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001252046,"about_ca_system_score_gemma":0.000002626354,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001058618,"about_ca_topic_score_gemma":0.00004447003,"domain_scores_codex":[0.9988551,0.000007572718,0.0003601772,0.0002591565,0.0001707058,0.0003473065],"domain_scores_gemma":[0.9996233,0.000180578,0.00008155392,0.00007070934,0.000005286902,0.00003858871],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.00006466239,0.00001566042,0.07783138,0.0004263383,0.0002318658,0.000001553322,0.001644228,0.8602629,0.04697862,0.003283908,0.0001904291,0.009068463],"study_design_scores_gemma":[0.001091409,0.00005977035,0.894573,0.0002673609,0.00003237023,0.000005786586,0.001330789,0.07654866,0.02286012,0.002450454,0.000319891,0.0004603356],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9985126,0.0002242901,0.0001154497,0.00002700262,0.0004817538,0.0003215911,0.00006930273,0.00009518303,0.000152822],"genre_scores_gemma":[0.9971154,0.00015249,0.002453185,0.000007032225,0.00003648017,0.00009649648,0.00001500604,0.00004313055,0.00008077752],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8167417,"threshold_uncertainty_score":0.9731535,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03409663155899791,"score_gpt":0.261282224582223,"score_spread":0.2271855930232251,"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."}}