{"id":"W2914385283","doi":"10.1002/mren.201800080","title":"Nitroxide‐Mediated Polymerization of Bio‐Based Farnesene with a Functionalized Methacrylate","year":2019,"lang":"en","type":"article","venue":"Macromolecular Reaction Engineering","topic":"Advanced Polymer Synthesis and Characterization","field":"Chemistry","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; Faculty of Engineering, McGill University; McGill University","keywords":"Polymer chemistry; Glycidyl methacrylate; Polymerization; Monomer; Chemistry; Nitroxide mediated radical polymerization; Dispersity; Copolymer; Molar mass distribution; Radical polymerization; Methyl methacrylate; Chain transfer; Styrene; Polymer; 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":[],"consensus_categories":[],"category_scores_codex":[0.00005103587,0.0001952777,0.0002325449,0.0001384015,0.00002571846,0.00001498884,0.00007580614,0.00009851433,0.0006645898],"category_scores_gemma":[0.00003246581,0.0001885485,0.0000764931,0.0003139715,0.00001509221,0.0001462325,0.00001279448,0.0001135869,0.00002060517],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004709898,"about_ca_system_score_gemma":0.00002991308,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002089393,"about_ca_topic_score_gemma":5.30539e-7,"domain_scores_codex":[0.9990296,0.00001237867,0.0002617172,0.0002524447,0.0002552574,0.0001885858],"domain_scores_gemma":[0.9993512,0.00005354034,0.000194709,0.000270098,0.00007028683,0.0000601597],"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":[0.0001022398,0.00004036308,0.0007325273,0.0001204766,0.0000699833,0.000004395382,0.00001852997,0.005638314,0.9916931,0.00007647708,4.354712e-7,0.001503091],"study_design_scores_gemma":[0.0007706939,0.00002760089,0.0009787015,0.0001030709,0.00004236789,0.00001371199,0.00002137601,0.0276654,0.9671658,0.000002260182,0.002980926,0.0002280454],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8882601,0.0001265008,0.1104218,0.00003670232,0.0001065754,0.00009055225,0.0000200664,0.0001798847,0.0007578645],"genre_scores_gemma":[0.9982106,0.00001118352,0.001066221,0.00002631151,0.00003578213,0.0000259421,0.000294955,0.00006232489,0.0002666684],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1099505,"threshold_uncertainty_score":0.7688786,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00321363509086049,"score_gpt":0.1763377166784888,"score_spread":0.1731240815876283,"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."}}