{"id":"W1986647245","doi":"10.2202/1934-2659.1145","title":"Modeling and Simulation of Viscoelastic Behavior of Three-Phase Polymer Blends with Multiple Droplet Morphology","year":2008,"lang":"en","type":"article","venue":"Chemical Product and Process Modeling","topic":"Advanced Polymer Synthesis and Characterization","field":"Chemistry","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Viscoelasticity; Materials science; Polymer; Morphology (biology); Phase (matter); Work (physics); Relaxation (psychology); Polymer blend; Rheology; Chemical engineering; Composite material; Thermodynamics; Copolymer; Chemistry; Organic chemistry","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":[0.00003655905,0.0001642016,0.0002893956,0.00004178773,0.00006591696,0.000004814919,0.00006612932,0.00008248909,0.00001985972],"category_scores_gemma":[0.00005205828,0.000141322,0.00002339334,0.00007937913,0.0001216201,0.0001674524,0.00003126863,0.0001148321,1.021354e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006303413,"about_ca_system_score_gemma":0.00003921607,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001502574,"about_ca_topic_score_gemma":7.791674e-7,"domain_scores_codex":[0.9990048,0.000004401722,0.0003440646,0.0003433011,0.0001429398,0.0001604498],"domain_scores_gemma":[0.9994855,0.00003644914,0.0001271048,0.0001584265,0.000132892,0.00005963726],"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":[0.0002834313,0.0001255467,0.002288616,0.0003445474,0.00001516472,0.000001629349,0.000445336,0.1076588,0.8842766,0.000003718454,4.914421e-8,0.004556546],"study_design_scores_gemma":[0.0003930302,0.00001554606,0.000002318745,0.0000521467,0.00004232816,0.00001433523,0.00003892454,0.5133469,0.4859773,0.00002708819,1.535757e-7,0.00008999347],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9141497,0.001213951,0.08448645,0.00001474673,0.00001074788,0.00006729222,0.00001641115,0.00002287707,0.00001783076],"genre_scores_gemma":[0.9991964,0.00006212422,0.0005587944,0.000004868909,0.00007361171,0.00002028345,0.00004823634,0.00002695944,0.000008767897],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4056881,"threshold_uncertainty_score":0.5762945,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02562455151794428,"score_gpt":0.2718507296757016,"score_spread":0.2462261781577573,"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."}}