{"id":"W2965739913","doi":"10.1016/j.polymer.2019.121684","title":"Effects of polymer-filler interactions on controlling the conductive network formation in polyamide 6/multi-Walled carbon nanotube composites","year":2019,"lang":"en","type":"article","venue":"Polymer","topic":"Carbon Nanotubes in Composites","field":"Materials Science","cited_by":56,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Materials science; Composite material; Carbon nanotube; Percolation threshold; Polyamide; Percolation (cognitive psychology); Differential scanning calorimetry; Transmission electron microscopy; Nanocomposite; Polymer; Nanotube; Scanning electron microscope; Electrical resistivity and conductivity; Nanotechnology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003124356,0.0004315186,0.0002250304,0.0001802281,0.0002920178,0.0004754118,0.0002429029,0.000264411,0.001532721],"category_scores_gemma":[0.0004972822,0.0002895926,0.0001757972,0.0001769051,0.0002693911,0.0004543822,0.0001454228,0.0003523921,0.0002380269],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002753251,"about_ca_system_score_gemma":0.0001901182,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007147572,"about_ca_topic_score_gemma":0.001761712,"domain_scores_codex":[0.9997417,0.00004742655,0.00002665396,0.00006552289,0.00005935,0.0000592303],"domain_scores_gemma":[0.9995328,0.0002064038,0.0001317721,0.00002227912,0.0000481323,0.00005865345],"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":[0.0002393163,0.00003712396,0.00008291889,0.00004902569,0.000008162443,0.00004044614,0.00002845616,0.0002585877,0.9982737,0.0000552243,0.00002169566,0.0009052579],"study_design_scores_gemma":[0.000004391902,0.00008127093,0.0004809059,0.000002046206,0.0000105725,0.00001015472,0.000006577928,0.000782873,0.9983979,0.00000633332,0.0002121205,0.000004792606],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9977186,0.0004339544,0.0006635329,0.00001882741,0.00002208747,0.000007498132,0.00003142929,0.00003228844,0.001071834],"genre_scores_gemma":[0.9986038,0.0001890655,0.0006496999,0.00001150063,0.000009218832,0.00000900641,0.00002690516,0.000021492,0.0004794303],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001532721,"threshold_uncertainty_score":0.00512749,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01016272887279294,"score_gpt":0.2460686655646484,"score_spread":0.2359059366918555,"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."}}