{"id":"W2334408208","doi":"10.1021/ma1026302","title":"High Solids Nitroxide-Mediated Microemulsion Polymerization of MMA with a Small Amount of Styrene and Synthesis of (MMA-<i>co</i>-St)-<i>block</i>-(BMA-<i>co</i>-St) Polymers","year":2011,"lang":"en","type":"article","venue":"Macromolecules","topic":"Advanced Polymer Synthesis and Characterization","field":"Chemistry","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Styrene; Microemulsion; Polymer chemistry; Methyl methacrylate; Polymerization; Nitroxide mediated radical polymerization; Monomer; Polymer; Copolymer; Materials science; Particle size; Molar mass distribution; Emulsion polymerization; Radical polymerization; Chemistry; Pulmonary surfactant; Physical chemistry; Composite material","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001255175,0.0005163873,0.0009064993,0.0002562898,0.0001000206,0.00001953919,0.0003713634,0.0002700271,0.0004136553],"category_scores_gemma":[0.00009014796,0.0004731342,0.0001550033,0.0003453,0.0005208091,0.0001831825,0.0001026931,0.0001652946,0.0000025288],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003581681,"about_ca_system_score_gemma":0.00008981483,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006680497,"about_ca_topic_score_gemma":0.00003580995,"domain_scores_codex":[0.997406,0.0001028753,0.001007619,0.0005828497,0.0004273517,0.00047331],"domain_scores_gemma":[0.9975759,0.0002113603,0.001202056,0.0006453148,0.0001873675,0.0001779358],"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":[0.0007074454,0.0004324535,0.005561839,0.0005530457,0.0002178968,0.00001449747,0.0007381204,0.00000446376,0.9844226,0.0001463474,0.000008893301,0.007192444],"study_design_scores_gemma":[0.001005234,0.0001879872,0.002614964,0.0005121756,0.0002409076,0.00003033688,0.0005586754,0.00004562397,0.9941775,0.00004001696,0.0001268896,0.0004596654],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.994575,0.0006899332,0.001573033,0.0000412454,0.000045384,0.0001754936,0.001447496,0.00007575339,0.001376693],"genre_scores_gemma":[0.9960312,0.0004063446,0.002832942,0.00005154768,0.00004667709,0.00003960819,0.0003778832,0.0001153418,0.0000984249],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00975497,"threshold_uncertainty_score":0.999772,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009273675466112465,"score_gpt":0.1986866021548803,"score_spread":0.1894129266887679,"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."}}