{"id":"W2963052345","doi":"","title":"Performance Evaluation of Nanocoolants for Automotive Cooling Application","year":2019,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Nanofluid Flow and Heat Transfer","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Nanofluid; Thermal conductivity; Materials science; Coolant; Heat transfer; Composite material; Heat transfer coefficient; Radiator (engine cooling); Zeta potential; Viscosity; Thermodynamics; Nanoparticle; Nanotechnology; Mechanical engineering","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":[0.0002668516,0.0003356714,0.0002818123,0.0002695961,0.0002265704,0.0002947834,0.0002885283,0.0002644138,0.001021442],"category_scores_gemma":[0.0003896709,0.00009381914,0.0003238419,0.000191406,0.00009543521,0.0002382146,0.0001806326,0.0002125156,0.0003512416],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003156153,"about_ca_system_score_gemma":0.0001687087,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001122638,"about_ca_topic_score_gemma":0.001757697,"domain_scores_codex":[0.9997999,0.00002195965,0.00001369142,0.00003880149,0.00009314955,0.00003239158],"domain_scores_gemma":[0.9998285,0.00002542027,0.00002312367,0.000008222084,0.0001022943,0.00001251988],"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":[0.0001830808,0.00002742648,0.0002609973,0.0001671565,0.000008137492,0.0000441922,0.00002908093,0.0007761615,0.9916769,0.0001107418,0.0002183347,0.006497657],"study_design_scores_gemma":[0.000004189483,0.0003620131,0.0007456445,0.000008444679,0.00001270779,0.00003702285,0.000020652,0.002267542,0.9942929,0.00001238982,0.002229939,0.000006676928],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9827154,0.005375579,0.006673432,0.0001250384,0.0001289756,0.00006821314,0.0003280948,0.0001765476,0.004408767],"genre_scores_gemma":[0.9873756,0.001640159,0.006789751,0.00003817461,0.00001874102,0.00007005013,0.0002146105,0.00005623852,0.003796674],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001122638,"threshold_uncertainty_score":0.003417075,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01261155562424584,"score_gpt":0.2590264226409874,"score_spread":0.2464148670167415,"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."}}