{"id":"W2949339324","doi":"10.1021/acs.macromol.9b00806","title":"Tuning Morphology and Thermal Transport of Asymmetric Smart Polymer Blends by Macromolecular Engineering","year":2019,"lang":"en","type":"article","venue":"Macromolecules","topic":"Thermal properties of materials","field":"Materials Science","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Compute Canada","keywords":"Polymer chemistry; Acrylic acid; Hydrogen bond; Polymer; Monomer; Context (archaeology); Chemical engineering; Solubility; van der Waals force; Materials science; Phase (matter); Macromolecule; Chemistry; Molecule; Physical chemistry; Organic chemistry","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003466332,0.0002464296,0.0004159508,0.000120902,0.00004078204,0.00003344348,0.0003413972,0.0001181568,0.00137641],"category_scores_gemma":[0.00002378427,0.0002237312,0.00006739904,0.0001212583,0.0001148896,0.0001388141,0.0001217559,0.00009376911,0.0001845711],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001724838,"about_ca_system_score_gemma":0.00002579442,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002259849,"about_ca_topic_score_gemma":6.558035e-7,"domain_scores_codex":[0.998461,0.00008318631,0.0003849984,0.0003936117,0.000243483,0.0004337188],"domain_scores_gemma":[0.99935,0.00004314896,0.0001295152,0.0003465284,0.000037482,0.00009339651],"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":[0.00006545798,0.0000278504,0.001172438,0.0001000919,0.00002189742,0.00003560663,0.0001439678,0.00005437341,0.9976872,0.0002300046,0.00001951307,0.0004415798],"study_design_scores_gemma":[0.000462985,0.0001307469,0.001743748,0.00004138998,0.00002584496,0.00005189833,0.0000384373,0.00006265892,0.9968832,0.000006225173,0.0002943409,0.0002584857],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9962505,0.001802509,0.0002509625,0.00006907589,0.0003324247,0.000188142,0.00008073047,0.00008819933,0.0009374864],"genre_scores_gemma":[0.9989347,0.00001742019,0.0005620074,0.0001112741,0.00002359491,0.00001208576,0.00001545889,0.00005699524,0.0002663968],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002684297,"threshold_uncertainty_score":0.9995365,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005347458991947238,"score_gpt":0.1881009024593941,"score_spread":0.1827534434674469,"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."}}