{"id":"W4404993695","doi":"10.21741/9781644903377-18","title":"Analysis of Al7136 surface roughness in end milling process based on discriminant analysis","year":2024,"lang":"en","type":"article","venue":"Materials research proceedings","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Science North","funders":"","keywords":"Surface roughness; Linear discriminant analysis; Process (computing); End milling; Surface finish; Materials science; Computer science; Artificial intelligence; Composite material; Metallurgy; Machining","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":[0.0005666996,0.0002636719,0.0004893529,0.0006364884,0.0001584048,0.0003399641,0.0002554885,0.0002988643,0.0005268744],"category_scores_gemma":[0.00101153,0.0001380823,0.0003732821,0.0003688739,0.0002338728,0.0002339972,0.0001798755,0.0003558209,0.0001819086],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001998489,"about_ca_system_score_gemma":0.0001144965,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006814548,"about_ca_topic_score_gemma":0.000937939,"domain_scores_codex":[0.999514,0.0000710208,0.00001994254,0.000104258,0.0002507413,0.00004013414],"domain_scores_gemma":[0.9990102,0.0004052262,0.0001256169,0.00007698188,0.0003458347,0.00003603422],"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":[0.0005958131,0.00009285215,0.008829446,0.00009928434,0.00001801613,0.00004604535,0.00009437121,0.003126927,0.9472759,0.00008886416,0.00008380417,0.03964875],"study_design_scores_gemma":[0.00003881065,0.0013002,0.1573495,0.00001018109,0.00006986396,0.0002298601,0.0001785969,0.09627848,0.7436939,0.0001709474,0.0006154873,0.00006407483],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9687666,0.0001558843,0.03054331,0.00001209361,0.00000957452,0.00001799196,0.00006742799,0.00006046841,0.0003666582],"genre_scores_gemma":[0.9840193,0.00005300827,0.01539227,0.000005904385,0.000002438506,0.00001177269,0.00009308228,0.00001058632,0.0004115644],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0006814548,"threshold_uncertainty_score":0.002997041,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03472211955899926,"score_gpt":0.359919732302618,"score_spread":0.3251976127436187,"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."}}