{"id":"W4200025104","doi":"10.1139/tcsme-2021-0139","title":"Sliding-friction wear of a seashell particulate reinforced polymer matrix composite: modeling and optimization through RSM and Grey Wolf optimizer","year":2021,"lang":"en","type":"article","venue":"Transactions of the Canadian Society for Mechanical Engineering","topic":"Tribology and Wear Analysis","field":"Engineering","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Materials science; Composite material; Response surface methodology; Composite number; Polymer; Tribology; Computer science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006435731,0.0008217456,0.0008681638,0.0006668838,0.0002968835,0.0006551388,0.0005769749,0.001301415,0.0007842021],"category_scores_gemma":[0.0007441463,0.0004408115,0.001199979,0.0003882254,0.0004739196,0.0003259364,0.0003775922,0.0005316447,0.00010185],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006133363,"about_ca_system_score_gemma":0.0007923605,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00958157,"about_ca_topic_score_gemma":0.006250443,"domain_scores_codex":[0.9998637,0.00004016473,0.00000796345,0.00002736814,0.00003606098,0.00002465726],"domain_scores_gemma":[0.9995758,0.000299389,0.00004662559,0.00001556822,0.00004858375,0.00001403902],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001150604,0.00001224835,0.0003040088,0.00003044944,0.00001055177,0.00002619237,0.000007755604,0.997315,0.0008614183,0.000170826,0.00002466823,0.001225409],"study_design_scores_gemma":[0.000001699891,0.00001075034,0.00008690669,0.000001636518,0.000003012719,0.000002127995,0.000003240302,0.9996169,0.0001911751,0.00003998075,0.0000411451,0.000001324307],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6707006,0.001432209,0.3187281,0.0002871307,0.00006861069,0.0001337153,0.0002016478,0.0002899397,0.008158065],"genre_scores_gemma":[0.9522841,0.0003248325,0.0442334,0.00004738351,0.00001132119,0.0002292328,0.000114787,0.00004297535,0.00271193],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00958157,"threshold_uncertainty_score":0.01905161,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008364494422135448,"score_gpt":0.1990626573846806,"score_spread":0.1906981629625452,"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."}}