{"id":"W2050655524","doi":"10.1016/j.progpolymsci.2011.08.001","title":"ATRP in the design of functional materials for biomedical applications","year":2011,"lang":"en","type":"article","venue":"Progress in Polymer Science","topic":"Advanced Polymer Synthesis and Characterization","field":"Chemistry","cited_by":611,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"National Institute of Biomedical Imaging and Bioengineering; Natural Sciences and Engineering Research Council of Canada; Israel National Road Safety Authority; Korea Science and Engineering Foundation; Canada Research Chairs; Concordia University; Ministry of Education, Science and Technology; National Science Foundation","keywords":"Nanotechnology; Atom-transfer radical-polymerization; Drug delivery; Materials science; Self-healing hydrogels; Polymer; Nanomaterials; Copolymer; Polymer 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001059682,0.0004193244,0.0003488461,0.0003429943,0.0002734486,0.0004988434,0.0007659114,0.0008945756,0.002321166],"category_scores_gemma":[0.0004412573,0.0003957862,0.0002382317,0.0003004754,0.0005304064,0.001401958,0.0005467958,0.001031948,0.001476932],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003526882,"about_ca_system_score_gemma":0.0002531603,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002072215,"about_ca_topic_score_gemma":0.0002586818,"domain_scores_codex":[0.9997798,0.00006539791,0.0000149261,0.00005570409,0.00005552165,0.00002866083],"domain_scores_gemma":[0.9998935,0.00005541581,0.00001608226,0.00001327312,0.00001375523,0.000007979303],"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":[0.0004391205,0.000179959,0.000280807,0.00209528,0.00003279494,0.0008624514,0.0002947581,0.009033036,0.683306,0.1037959,0.003534874,0.196145],"study_design_scores_gemma":[0.00007671114,0.000695713,0.0003202544,0.0001397421,0.00004003891,0.0007208122,0.00007539555,0.01274859,0.8420141,0.01479153,0.1283426,0.00003459878],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2836307,0.1674487,0.4583846,0.004889836,0.001094364,0.0003599509,0.0005155149,0.0009895267,0.08268687],"genre_scores_gemma":[0.7058001,0.08633683,0.1626231,0.001047899,0.0004983679,0.0004397506,0.0004107586,0.0002516978,0.04259153],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002321166,"threshold_uncertainty_score":0.007765055,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04805303598136729,"score_gpt":0.2870026933571911,"score_spread":0.2389496573758238,"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."}}