{"id":"W1161762893","doi":"","title":"Komputerowe wspomaganie klasyfikacji wad identyfikowanych metodami radiograficznymi w odlewach ze stopów aluminium","year":2005,"lang":"pl","type":"article","venue":"RUDY I METALE NIEŻELAZNE","topic":"Materials Engineering and Processing","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Windsor; Natural Sciences and Engineering Research Council of Canada","funders":"","keywords":"Aluminium; Physics; Materials science; Metallurgy","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":["metaepi_narrow","insufficient_payload"],"category_scores_codex":[0.001698644,0.001704645,0.002008296,0.0009263669,0.000442027,0.0009117896,0.001350351,0.0008926193,0.002124659],"category_scores_gemma":[0.0001370437,0.001873033,0.0007376618,0.001391103,0.0002111097,0.001254553,0.0003501012,0.001224449,0.002749472],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005031716,"about_ca_system_score_gemma":0.0001463976,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001034935,"about_ca_topic_score_gemma":0.0000255267,"domain_scores_codex":[0.992689,0.0003075686,0.002002321,0.001531783,0.001208167,0.002261217],"domain_scores_gemma":[0.9968234,0.0002849704,0.0004021501,0.001445608,0.0001849583,0.0008588743],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004220005,0.002337416,0.0008103347,0.008630334,0.006569643,0.0007222172,0.009642178,0.2530151,0.3856127,0.004891919,0.07715943,0.2501867],"study_design_scores_gemma":[0.005113092,0.0005378221,0.002767107,0.001296667,0.001990976,0.0007933446,0.0002677016,0.1802882,0.1897412,0.0003079438,0.611707,0.005188891],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7600909,0.09782197,0.07507495,0.003376205,0.02211398,0.002638106,0.0006021901,0.00621479,0.03206694],"genre_scores_gemma":[0.9600985,0.001825652,0.02316485,0.0004237866,0.005100588,0.00009611371,0.0001373422,0.0005928924,0.008560258],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5345476,"threshold_uncertainty_score":0.99957,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006629909025219951,"score_gpt":0.2029325165773131,"score_spread":0.1963026075520931,"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."}}