{"id":"W7135842424","doi":"","title":"How To Predict Truck Tyre Wear","year":2024,"lang":"en","type":"article","venue":"University of Twente Research Information","topic":"Polymer Nanocomposites and Properties","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"SKiN Health","funders":"","keywords":"Truck; Abrasion (mechanical); Durability; Work (physics); Natural rubber; Commercial vehicle","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":[0.0005622113,0.0007835471,0.0004427095,0.001144476,0.0001502638,0.001172495,0.0003787074,0.0007344487,0.002401775],"category_scores_gemma":[0.002267864,0.0004101684,0.0004883566,0.0004082022,0.0001395975,0.001091335,0.0002625348,0.0004794899,0.002309947],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002828554,"about_ca_system_score_gemma":0.0003489662,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004814975,"about_ca_topic_score_gemma":0.007417562,"domain_scores_codex":[0.9996963,0.00003936505,0.00002472614,0.0000758625,0.0001372057,0.00002666818],"domain_scores_gemma":[0.9989939,0.0003453993,0.0002281272,0.00009623533,0.0002962335,0.00004009077],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005266758,0.0002950485,0.2806107,0.0008218879,0.0001621266,0.0002786655,0.0001903522,0.1645855,0.1751729,0.0006975867,0.005255444,0.3714032],"study_design_scores_gemma":[0.00001244472,0.0005194165,0.1397488,0.000144207,0.00008670537,0.0002700706,0.0002656396,0.7767479,0.07344499,0.001024283,0.007634026,0.0001015097],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.81872,0.002428408,0.1655675,0.0003930886,0.0001340447,0.0001945609,0.00275053,0.003615314,0.006196573],"genre_scores_gemma":[0.9478714,0.001264004,0.04422317,0.0000487846,0.00002339802,0.00006639864,0.002030426,0.0001912302,0.004281143],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004814975,"threshold_uncertainty_score":0.009573936,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03066812558102826,"score_gpt":0.2617935979965992,"score_spread":0.231125472415571,"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."}}