{"id":"W4383334802","doi":"10.2139/ssrn.4502683","title":"A Comprehensive Study on Porosity Recognition of Overlap Aluminum Laser Welding; Experimental and Statistical Investigation","year":2023,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Welding Techniques and Residual Stresses","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"National Research Council Canada; Université du Québec à Rimouski","funders":"","keywords":"Porosity; Welding; Aluminium; Materials science; Metallurgy; Artificial intelligence; Computer science; Composite material","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":[0.001059127,0.0003276639,0.0005081687,0.001537045,0.0004743442,0.0005629127,0.0005762409,0.0004410502,0.0008365828],"category_scores_gemma":[0.003205189,0.0002100961,0.0003670114,0.001301332,0.0007864431,0.0007105224,0.0004204177,0.0002728769,0.0001574795],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002335902,"about_ca_system_score_gemma":0.0005261164,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001593896,"about_ca_topic_score_gemma":0.001520798,"domain_scores_codex":[0.9989537,0.0001586613,0.00007258205,0.0002475704,0.0004864208,0.00008097822],"domain_scores_gemma":[0.9962221,0.001716256,0.0005385034,0.0004896931,0.0009568118,0.00007661805],"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":[0.001179618,0.0006277697,0.1760751,0.0005535955,0.0001759478,0.0004589884,0.0008718172,0.08360648,0.5194723,0.00266898,0.0004750718,0.2138343],"study_design_scores_gemma":[0.00001549011,0.0009636108,0.2013702,0.00002882627,0.0002133441,0.001157032,0.0007888108,0.3337137,0.4583525,0.001527955,0.001749014,0.0001195409],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9416142,0.0002492772,0.05727507,0.000009969884,0.000004022047,0.00001888204,0.0001506233,0.0001178014,0.0005602767],"genre_scores_gemma":[0.9952652,0.0000624266,0.004283475,0.000002096375,0.000003583489,0.000008727769,0.0001677362,0.00001408826,0.0001926906],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001593896,"threshold_uncertainty_score":0.005601287,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03632022183948561,"score_gpt":0.2828729556912498,"score_spread":0.2465527338517642,"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."}}