{"id":"W2002193426","doi":"10.1021/ma0506738","title":"Nonlinear Rheology of Multiarm Star Chains","year":2005,"lang":"en","type":"article","venue":"Macromolecules","topic":"Rheology and Fluid Dynamics Studies","field":"Chemical Engineering","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Viscoelasticity; Micelle; Polystyrene; Copolymer; Materials science; Rheology; Relaxation (psychology); Star (game theory); Polymer chemistry; Composite material; Chemical physics; Physics; Chemistry; Astrophysics; Aqueous solution; Physical 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":[0.00007390053,0.0001282894,0.0002262462,0.00005456587,0.00004214151,0.000002085051,0.0001569107,0.0001090675,0.0001119829],"category_scores_gemma":[0.00008661734,0.0001217971,0.00007331562,0.00006568419,0.0001615908,0.00002764668,0.0001036283,0.0001451941,0.00007374534],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000194543,"about_ca_system_score_gemma":0.000007983785,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002405004,"about_ca_topic_score_gemma":0.0000379651,"domain_scores_codex":[0.999257,0.00001801972,0.0002283057,0.000172503,0.00007779273,0.0002463969],"domain_scores_gemma":[0.9996142,0.00007123094,0.0000460104,0.0001861676,0.00004120472,0.00004120178],"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":[0.00005676153,0.0002321947,0.002779829,0.00006365235,0.0002018627,0.00002991563,0.0007857789,0.002815915,0.758934,0.230667,0.0001958037,0.003237325],"study_design_scores_gemma":[0.0005300798,0.00005092096,0.0006971137,0.00001429585,0.00002093891,0.00001430304,0.00005118374,0.8900167,0.1075197,0.00006934351,0.0008356296,0.0001798502],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8781565,0.0008186083,0.1167416,0.0005993645,0.0001029463,0.00007597129,0.00003486788,0.0001079937,0.003362091],"genre_scores_gemma":[0.9637297,0.00009422987,0.03159713,0.000148198,0.00009947961,0.00000819588,0.00001626954,0.00001973065,0.004287108],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8872008,"threshold_uncertainty_score":0.496674,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007470975556939497,"score_gpt":0.2301878691869696,"score_spread":0.2227168936300301,"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."}}