{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001887208,0.0003232022,0.0002059085,0.0003431514,0.00009360101,0.0002185909,0.0001604095,0.0002478427,0.0009700218],"category_scores_gemma":[0.0002439526,0.0001449688,0.0002019751,0.0001409104,0.0001132819,0.0002776672,0.0001456644,0.0002941282,0.000235657],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001015202,"about_ca_system_score_gemma":0.00008717302,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003696931,"about_ca_topic_score_gemma":0.001081423,"domain_scores_codex":[0.9998083,0.00003102759,0.00001450843,0.00003343104,0.00007962746,0.00003315975],"domain_scores_gemma":[0.9998245,0.00004099324,0.00005659711,0.00001285676,0.00003866341,0.00002646977],"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":[0.00004557074,0.00001740502,0.0001209471,0.00004653833,0.000005295252,0.00002426674,0.00001144382,0.00005817858,0.9979858,0.00001838286,0.00001323424,0.001652792],"study_design_scores_gemma":[0.000005269783,0.0004649822,0.001919169,0.000004537736,0.00001281174,0.00007149242,0.00001235413,0.0003859532,0.9961824,0.000004965501,0.0009328002,0.000003297781],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9962276,0.001412581,0.001095729,0.00002557567,0.00001053392,0.00001640922,0.00004134369,0.00003771572,0.001132405],"genre_scores_gemma":[0.9934728,0.001212768,0.003349854,0.00003442326,0.00000884506,0.000009209625,0.00008361603,0.00002676538,0.00180173],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009700218,"threshold_uncertainty_score":0.003245115,"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."}}