{"id":"W2086908499","doi":"10.1002/pc.22319","title":"Preparation and properties of polyester nanocomposites: Effects of mixing","year":2012,"lang":"en","type":"article","venue":"Polymer Composites","topic":"Polymer Nanocomposites and Properties","field":"Materials Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Materials science; Thermosetting polymer; Mixing (physics); Nanocomposite; Composite material; Viscoelasticity; Microstructure; Thermoplastic; Polyester; Dispersion (optics); Nanoparticle; Nanotechnology","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":[0.0003794878,0.0005198142,0.0002552343,0.0002609852,0.0001653684,0.0002653186,0.0001484535,0.0002579589,0.000947207],"category_scores_gemma":[0.0006448624,0.0002018186,0.0002104915,0.0001738877,0.0001778036,0.0002856151,0.0002013151,0.0004222902,0.0002499953],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001449487,"about_ca_system_score_gemma":0.00011754,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002208345,"about_ca_topic_score_gemma":0.0004268653,"domain_scores_codex":[0.9997045,0.00004165067,0.00003885499,0.00008186348,0.00009466942,0.00003847047],"domain_scores_gemma":[0.9994904,0.0001608127,0.0001600157,0.00004609238,0.00008703819,0.00005553247],"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":[0.00002732608,0.000008156539,0.00004993104,0.00001560625,0.000002206888,0.00001127571,0.00001289617,0.00004450689,0.9993846,0.000006888601,0.000002931564,0.000433638],"study_design_scores_gemma":[0.000002003389,0.0000611687,0.0003959859,0.000001454532,0.000004693952,0.00001807945,0.000003635461,0.0002316234,0.9991457,0.000003454171,0.0001304443,0.000001734837],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9919752,0.0008204014,0.005906676,0.00002913885,0.00001912458,0.00003745372,0.0001256887,0.0001131059,0.0009731175],"genre_scores_gemma":[0.9943113,0.0002454793,0.004274933,0.00001299848,0.000004836008,0.00003275333,0.000131047,0.00004893552,0.0009377015],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.000947207,"threshold_uncertainty_score":0.003168702,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01305974432451338,"score_gpt":0.2344051989817213,"score_spread":0.2213454546572079,"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."}}