{"id":"W1577753418","doi":"10.1016/j.ces.2007.06.010","title":"Rheological properties of water-based <mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" altimg=\"si37.gif\" display=\"inline\" overflow=\"scroll\"><mml:msub><mml:mrow><mml:mi>Fe</mml:mi></mml:mrow><mml:mrow><mml:mn>3</mml:mn></mml:mrow></mml:msub><mml:msub><mml:mrow><mml:mi mathvariant=\"normal\">O</mml:mi></mml:mrow><mml:mrow><mml:mn>4</mml:mn></mml:mrow></mml:msub></mml:math> ferrofluids","year":2007,"lang":"lv","type":"article","venue":"Chemical Engineering Science","topic":"Characterization and Applications of Magnetic Nanoparticles","field":"Engineering","cited_by":131,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of New Brunswick","funders":"National Science Foundation","keywords":"Rheometer; Rheology; Materials science; Magnetic field; Viscosity; Ball mill; Composite material; Analytical Chemistry (journal); Thermodynamics; Physics; Chemistry; Chromatography","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":[0.0002648078,0.0004016169,0.0002206766,0.0003094524,0.000376441,0.0003284972,0.0004714161,0.0004286334,0.01026395],"category_scores_gemma":[0.001316218,0.0001894396,0.0001706286,0.000434817,0.0003336581,0.000601103,0.0001657823,0.0009733035,0.001593281],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003568902,"about_ca_system_score_gemma":0.0003086622,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003463921,"about_ca_topic_score_gemma":0.003615951,"domain_scores_codex":[0.9998068,0.00002224645,0.00001551475,0.00003862347,0.00006106486,0.0000558143],"domain_scores_gemma":[0.9996848,0.0001044311,0.00004491807,0.00002264727,0.00010446,0.00003865517],"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":[0.0007874609,0.00008541023,0.0006659261,0.000223465,0.00002989179,0.0001756967,0.0003109836,0.001201829,0.9830415,0.001145595,0.002764693,0.009567513],"study_design_scores_gemma":[0.00001729972,0.000142758,0.001760155,0.00002232467,0.00001226397,0.00004413158,0.00009215037,0.002533621,0.9910365,0.0001116247,0.004206405,0.00002078605],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9760541,0.002204252,0.004808768,0.0003328853,0.0002295338,0.0000538912,0.003328971,0.0003050857,0.01268251],"genre_scores_gemma":[0.9759713,0.001093021,0.002967417,0.00009995206,0.00002320258,0.00005522789,0.003837998,0.0001413394,0.01581066],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01026395,"threshold_uncertainty_score":0.03433633,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01517466354344548,"score_gpt":0.2216043473727134,"score_spread":0.2064296838292679,"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."}}