{"id":"W4297910439","doi":"10.1016/j.ijadhadh.2022.103255","title":"Are probabilistic methods a way to get rid of fudge factors? Part I: Background and theory","year":2022,"lang":"en","type":"article","venue":"International Journal of Adhesion and Adhesives","topic":"Mechanical Behavior of Composites","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Northern British Columbia","funders":"","keywords":"Probabilistic logic; Dimensioning; Fibre-reinforced plastic; Variety (cybernetics); Computer science; Structural engineering; Materials science; Mechanical engineering; Engineering; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004846676,0.0001163421,0.0002439624,0.0001853129,0.00004681123,0.00003619062,0.0002479941,0.0000276395,0.0002962924],"category_scores_gemma":[0.0002014787,0.0000973833,0.00007951345,0.00006357499,0.00003483292,0.0001194311,0.0001442067,0.0001887279,0.000001043145],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004263051,"about_ca_system_score_gemma":0.00001101882,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001286871,"about_ca_topic_score_gemma":6.131414e-7,"domain_scores_codex":[0.9988995,0.0001603351,0.0003937985,0.000105076,0.0003445639,0.0000967625],"domain_scores_gemma":[0.9989302,0.0005041481,0.0002153761,0.00007743991,0.0001435817,0.0001292668],"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":[0.0007451109,0.0003688151,0.01021986,0.0001465618,0.0005606765,0.0001687074,0.002200744,0.002265319,0.9223238,0.0135584,0.001845536,0.04559648],"study_design_scores_gemma":[0.003120084,0.00254376,0.2420167,0.0008352479,0.0004357755,0.0009924142,0.008027817,0.002207243,0.6548448,0.04335656,0.04044953,0.00117008],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9956276,0.0008993181,0.002432315,0.0002519019,0.0005938742,0.0000800768,0.00003175913,0.00001518644,0.00006790341],"genre_scores_gemma":[0.9944348,0.0000788589,0.005256067,0.00008541267,0.00007485429,0.000004842533,0.000001947345,0.00001486038,0.00004837755],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2674791,"threshold_uncertainty_score":0.3971176,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04548581843339376,"score_gpt":0.3271284586000478,"score_spread":0.281642640166654,"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."}}