{"id":"W2973223109","doi":"10.1016/j.mtla.2019.100468","title":"Liquid–liquid interfacial films: A tunable one-pot nanocomposite preparation method and platform technology","year":2019,"lang":"en","type":"article","venue":"Materialia","topic":"Advanced Sensor and Energy Harvesting Materials","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Innovates; Canada Excellence Research Chairs, Government of Canada","keywords":"Materials science; Nanocomposite; Polymer; Nanoparticle; Chemical engineering; Polystyrene; Polymer nanocomposite; Methacrylate; Methyl methacrylate; Fabrication; Nanotechnology; Composite material; Copolymer","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001412753,0.0002016571,0.0003129542,0.0001243952,0.0000552227,0.00009685269,0.0001198534,0.0001832698,0.0004305592],"category_scores_gemma":[0.00001592345,0.000207342,0.00002387289,0.0001021867,0.00002946609,0.0002784072,0.00008505593,0.00006784602,0.0001812001],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003853123,"about_ca_system_score_gemma":0.000006938778,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003746709,"about_ca_topic_score_gemma":0.00000602016,"domain_scores_codex":[0.9990397,0.00002337224,0.000306544,0.0002497218,0.00008281365,0.0002978281],"domain_scores_gemma":[0.9996146,0.00001138158,0.00005274009,0.0002432621,0.00002772244,0.00005029736],"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":[0.0003668137,0.000008576761,0.00001373215,0.0001214216,0.00002626787,0.000002466785,0.0001662672,0.003457423,0.9945738,0.000925154,0.0001866187,0.0001514695],"study_design_scores_gemma":[0.0003786667,0.0003484959,0.00004307895,0.00007818584,0.00001503084,0.00002292525,0.00002927908,0.0009577116,0.9834095,0.000337917,0.01411696,0.0002623091],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9898879,0.00003722919,0.004511141,0.00002364374,0.002426677,0.0002274588,0.00002456457,0.0006643914,0.002196988],"genre_scores_gemma":[0.9848219,0.00001872292,0.01378024,0.00002411982,0.0001164725,0.00004496942,0.00003198443,0.00005104724,0.001110594],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01393034,"threshold_uncertainty_score":0.8455161,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01194346706026953,"score_gpt":0.250427792370295,"score_spread":0.2384843253100255,"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."}}