{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005356929,0.00004501302,0.00006745831,0.0003158605,0.0001526557,0.0002205671,0.0002735679,0.00003462903,0.0002097949],"category_scores_gemma":[0.00004323034,0.00004129394,0.00003444524,0.0002849838,0.00008726026,0.001706592,0.0001884692,0.00009733865,0.0006610975],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007188218,"about_ca_system_score_gemma":0.00008454395,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003288615,"about_ca_topic_score_gemma":0.00001111193,"domain_scores_codex":[0.9991559,0.0000589263,0.00007416592,0.00007628367,0.0004327155,0.0002020146],"domain_scores_gemma":[0.9995786,0.0000418356,0.0000194643,0.0001298292,0.0001392469,0.00009100213],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0007012457,0.0000554611,0.0005618372,0.001346614,0.00005909425,0.00002565827,0.02912665,0.0002510904,0.7001345,0.009532045,0.1481076,0.1100982],"study_design_scores_gemma":[0.0002119002,0.0002679967,0.0004732056,0.0002127719,0.000006913562,0.000004051504,0.004043045,0.003643994,0.1518444,0.00008485264,0.8391113,0.00009558124],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9689497,0.0004242746,0.004965259,0.007868187,0.0003967315,0.0005016329,0.0001826963,0.000171563,0.01653996],"genre_scores_gemma":[0.994372,0.00007781788,0.0007107431,0.00002025259,0.00002963906,3.685394e-7,0.0000146483,0.000002765138,0.004771839],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6910036,"threshold_uncertainty_score":0.8497292,"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."}}