{"id":"W3151180770","doi":"10.11159/iccpe17.121","title":"Improving the Abrasion Resistance of “Green” Tyre Compounds","year":2017,"lang":"en","type":"article","venue":"Proceedings of the World Congress on Mechanical, Chemical, and Material Engineering","topic":"Catalytic Processes in Materials Science","field":"Materials Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Loughborough University","keywords":"Abrasion (mechanical); Materials science; Composite material; Resistance (ecology); Computer science; Agronomy","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007620302,0.0002502748,0.0004158699,0.00005439984,0.0003636892,0.0004147564,0.002042283,0.00008362871,0.00003732177],"category_scores_gemma":[0.0007333382,0.0001590491,0.00007617714,0.0001225436,0.0005309116,0.000358586,0.00111348,0.0001527486,0.000002336245],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003781854,"about_ca_system_score_gemma":0.00002813915,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005661685,"about_ca_topic_score_gemma":0.000008049051,"domain_scores_codex":[0.9982538,0.000006418163,0.0005055207,0.0004293365,0.0004600116,0.0003449615],"domain_scores_gemma":[0.9983495,0.000109246,0.0007216207,0.000548421,0.0001876093,0.00008361489],"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":[0.0001333201,0.00002360367,0.000007807018,0.0005820525,0.000006045952,3.487709e-7,0.00001278069,0.00000508592,0.9889318,0.01001652,0.0002134815,0.00006715705],"study_design_scores_gemma":[0.0002810565,0.00002424507,0.00003865084,0.0005755939,0.00003170596,0.000005890383,0.00002805379,0.0004722848,0.9969245,0.001012911,0.0004206515,0.0001844234],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9968157,0.00001415987,0.000003365049,0.0005265626,0.001956414,0.0002512642,0.00004038247,0.00006084477,0.000331248],"genre_scores_gemma":[0.9976983,0.00001677296,0.001611809,0.00004064676,0.000207662,0.00002847996,6.982876e-7,0.00002778453,0.0003678449],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009003612,"threshold_uncertainty_score":0.6485833,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008759977078671554,"score_gpt":0.2212290066146507,"score_spread":0.2124690295359792,"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."}}