{"id":"W4393382230","doi":"10.1007/978-981-97-0918-2_28","title":"Characterization of TiO2/Fe3O4 Reinforced Magnetorheological Fluid Blend","year":2024,"lang":"en","type":"book-chapter","venue":"Lecture notes in mechanical engineering","topic":"Vibration Control and Rheological Fluids","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Trinity College","funders":"","keywords":"Magnetorheological fluid; Materials science; Characterization (materials science); Composite material; Structural engineering; Engineering; Nanotechnology","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001608238,0.0005336368,0.0007572876,0.0002977869,0.0000175523,0.000032224,0.0002550099,0.0009633231,0.001103554],"category_scores_gemma":[0.0001576466,0.000461092,0.0002388052,0.000137326,0.00003327502,0.00008070919,0.00009465394,0.001039352,0.00008627684],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001101327,"about_ca_system_score_gemma":0.00001823911,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001211592,"about_ca_topic_score_gemma":0.000002567725,"domain_scores_codex":[0.9981773,0.000008484779,0.0007755313,0.0003959129,0.0002826909,0.0003600223],"domain_scores_gemma":[0.9993193,0.0002142522,0.0000507712,0.0002603533,0.00004645576,0.0001088246],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001783825,0.000003695021,1.994996e-7,0.0003759562,0.00007434787,0.00004925764,0.00001766085,0.2165087,0.5262644,0.2542874,0.000009434397,0.00239117],"study_design_scores_gemma":[0.0003321458,0.0001739648,0.000009661332,0.0005889255,0.00008249047,0.00002531795,2.399377e-7,0.9312235,0.0457467,0.01210414,0.009016682,0.0006962193],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001488043,0.001987108,0.9700817,0.0001908936,0.00180628,0.0005927327,0.00009016702,0.001167002,0.02259607],"genre_scores_gemma":[0.9758071,0.001239365,0.003317386,0.0001788555,0.001138055,0.00007445037,0.0003860834,0.0003304817,0.01752824],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.974319,"threshold_uncertainty_score":0.9998096,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006733572470319917,"score_gpt":0.1821308350435217,"score_spread":0.1753972625732018,"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."}}