{"id":"W2911281642","doi":"10.1016/j.eurpolymj.2019.01.041","title":"Synthesis of isoprenic polybutadiene macromonomers for the preparation of branched polybutadiene","year":2019,"lang":"en","type":"article","venue":"European Polymer Journal","topic":"Advanced Polymer Synthesis and Characterization","field":"Chemistry","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Macromonomer; Polybutadiene; Copolymer; Polymer chemistry; Isoprene; Tetrahydrofuran; Anionic addition polymerization; Solvent; Telechelic polymer; Materials science; Yield (engineering); Hexane; Molar mass distribution; End-group; Chemistry; Organic chemistry; Polymer; 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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003599651,0.0002044093,0.0003433731,0.00008721687,0.0001343202,0.00003525976,0.0004408841,0.00005132978,0.001283329],"category_scores_gemma":[0.0001053753,0.0001534434,0.0002924405,0.000119403,0.00009316529,0.0002243055,0.00005458672,0.0001624342,0.00002299993],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003280931,"about_ca_system_score_gemma":0.00005615748,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006666432,"about_ca_topic_score_gemma":9.730746e-7,"domain_scores_codex":[0.9983793,0.00009449521,0.000734268,0.0002214485,0.0002308932,0.0003395472],"domain_scores_gemma":[0.9980384,0.0003809075,0.000927985,0.0004509574,0.00009825879,0.0001034769],"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":[0.0003651829,0.00007713128,0.001423504,0.00008105666,0.0001972397,0.000001278377,0.0006372434,0.00004973088,0.937769,0.0001491106,0.00005866021,0.05919085],"study_design_scores_gemma":[0.0005365672,0.00007401456,0.002198914,0.0001356606,0.0001350888,0.00005429017,0.0002575527,0.000296501,0.9942112,0.00001738639,0.001910947,0.0001718831],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9800483,0.004381358,0.002943217,0.0002170251,0.0003924663,0.0001486128,0.0001289996,0.00002648095,0.01171357],"genre_scores_gemma":[0.9965124,0.0002738943,0.0001662183,0.0000454148,0.0003255945,0.000007523633,0.00001012745,0.0000635878,0.002595311],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05901896,"threshold_uncertainty_score":0.9996296,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00800053531754066,"score_gpt":0.2351965454734266,"score_spread":0.2271960101558859,"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."}}