{"id":"W2614492709","doi":"10.1002/macp.201700107","title":"Practical Chain‐End Reduction of Polymers Obtained with ATRP","year":2017,"lang":"en","type":"article","venue":"Macromolecular Chemistry and Physics","topic":"Advanced Polymer Synthesis and Characterization","field":"Chemistry","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dow Chemical (Canada)","funders":"California NanoSystems Institute; Division of Materials Research; Materials Research Science and Engineering Center, Harvard University; University of California, Santa Barbara; Dow Materials Institute, Dow Chemical Company; European Commission; National Institutes of Health; National Science Foundation; Lubrizol; Dow Chemical Company","keywords":"Polymer; Bromine; Halogenation; Polymer chemistry; Chemistry; Monomer; Halogen; Chlorine; Catalysis; Organic chemistry; Alkyl","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002314592,0.0007163133,0.0002262292,0.000223589,0.0001904762,0.0002336082,0.0003364822,0.0004073323,0.002687387],"category_scores_gemma":[0.0001868305,0.0002702912,0.0002550064,0.0001866754,0.0002138531,0.0003998476,0.0004557921,0.001240742,0.001289132],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001743077,"about_ca_system_score_gemma":0.0001800452,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001793587,"about_ca_topic_score_gemma":0.0003808943,"domain_scores_codex":[0.9997877,0.00002319096,0.00001089934,0.00004941902,0.00008200228,0.00004682903],"domain_scores_gemma":[0.9999015,0.00002640036,0.00002850607,0.00001951407,0.00001513044,0.000008965567],"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":[0.00001536473,0.00001092252,0.00001939093,0.00006146947,0.00000322479,0.00005331268,0.00002291518,0.00008899589,0.9962184,0.000156188,0.00008914913,0.003260761],"study_design_scores_gemma":[0.000002317071,0.00004493227,0.0001092161,0.000002617785,0.000002394406,0.0000653838,0.000003403903,0.0001877479,0.9974909,0.0000387585,0.0020499,0.000002543824],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8013295,0.004827876,0.1629159,0.0004570071,0.0001426482,0.0002184997,0.0008991387,0.001264957,0.02794459],"genre_scores_gemma":[0.9269791,0.003744199,0.05585452,0.0001961999,0.00004821824,0.0001620007,0.0009901703,0.0003252353,0.01170048],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002687387,"threshold_uncertainty_score":0.008990228,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009961252738312767,"score_gpt":0.2495586294230013,"score_spread":0.2395973766846885,"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."}}