{"id":"W1966137095","doi":"10.1002/pc.23398","title":"High thermally conductive PLA based composites with tailored hybrid network of hexagonal boron nitride and graphene nanoplatelets","year":2015,"lang":"en","type":"article","venue":"Polymer Composites","topic":"Additive Manufacturing and 3D Printing Technologies","field":"Engineering","cited_by":63,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Materials science; Composite material; Boron nitride; Thermal conductivity; Electrical conductor; Graphene; Composite number; Microelectronics; 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":[0.0001175436,0.0004072471,0.00015289,0.0003605318,0.0001608794,0.0002252956,0.0001537246,0.0002872416,0.0006678253],"category_scores_gemma":[0.0001362629,0.0002655757,0.0001950903,0.0001877324,0.0001879811,0.0004205698,0.0002005434,0.0002951827,0.0002762108],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002840463,"about_ca_system_score_gemma":0.0001132093,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003551861,"about_ca_topic_score_gemma":0.001651471,"domain_scores_codex":[0.9999125,0.00001018797,0.000004864456,0.0000257818,0.00003189022,0.00001474798],"domain_scores_gemma":[0.9998844,0.00002131546,0.00004779782,0.000009378859,0.00001926453,0.00001777779],"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":[0.00002006532,0.000009446865,0.0000382559,0.00002624327,0.000002648485,0.00001677534,0.000005695003,0.0002549084,0.9988587,0.00004985895,0.00001581308,0.0007015222],"study_design_scores_gemma":[0.000004043508,0.00009056892,0.0007527865,0.000002990138,0.000009447465,0.00006063514,0.000007398384,0.002505828,0.9958166,0.00002554143,0.0007179218,0.000006181817],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9879441,0.001025556,0.007603777,0.0000529639,0.00003775987,0.00002262133,0.0001385667,0.0002602987,0.002914304],"genre_scores_gemma":[0.988853,0.0003859059,0.00882875,0.00002780575,0.00000968907,0.00002234606,0.0001295484,0.0000380012,0.001704873],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0006678253,"threshold_uncertainty_score":0.002234161,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01144669234567763,"score_gpt":0.186098914208069,"score_spread":0.1746522218623914,"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."}}