{"id":"W4321599081","doi":"10.1002/cjce.24884","title":"On modelling of surface tension of <scp> CMC‐α‐Fe <sub>2</sub> O <sub>3</sub> </scp> nanoparticles by fuzzy‐hybrid approach: A comparison study","year":2023,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Rheology and Fluid Dynamics Studies","field":"Chemical Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Fuzzy logic; Surface tension; Carboxymethyl cellulose; Rheology; Representation (politics); Nanoparticle; Response surface methodology; Computer science; Biological system; Surface (topology); Experimental data; Materials science; Mathematics; Algorithm; Thermodynamics; Artificial intelligence; Machine learning; Nanotechnology; Physics; Statistics; Composite material; Geometry","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":[0.0003313829,0.0003866612,0.0003510122,0.000369118,0.0002424073,0.0006749553,0.0004539969,0.0009083447,0.0007303269],"category_scores_gemma":[0.0005901707,0.0001698238,0.0005941087,0.0001876855,0.000257594,0.0003658843,0.0002589283,0.0003051063,0.0001068278],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005130231,"about_ca_system_score_gemma":0.0003214188,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006676798,"about_ca_topic_score_gemma":0.003506436,"domain_scores_codex":[0.9998766,0.00003058261,0.000007589771,0.00003027561,0.00004403887,0.00001086264],"domain_scores_gemma":[0.9997101,0.0001556451,0.00003431381,0.00002016189,0.00007011435,0.000009650746],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005839327,0.00003596119,0.0006796894,0.00006903459,0.00002085192,0.00006568181,0.00004704998,0.9759413,0.01154491,0.001105498,0.00006292274,0.01036868],"study_design_scores_gemma":[0.000001140824,0.00001916419,0.0001470741,0.000002365129,0.000002925663,0.000005686005,0.000005844045,0.9985378,0.00109916,0.0001056955,0.00007071386,0.000002357915],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4884491,0.0005520354,0.5007487,0.0001800838,0.00003934681,0.00007876078,0.0001120804,0.0002610365,0.009578804],"genre_scores_gemma":[0.9873181,0.00009858613,0.01145915,0.000007446673,0.000003161295,0.00002827996,0.00002417142,0.00000661487,0.001054597],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006676798,"threshold_uncertainty_score":0.01327586,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01873029533124045,"score_gpt":0.2006169532296665,"score_spread":0.181886657898426,"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."}}