{"id":"W2060975926","doi":"10.1021/ja209793b","title":"Near-Infrared Light-Triggered Dissociation of Block Copolymer Micelles Using Upconverting Nanoparticles","year":2011,"lang":"en","type":"article","venue":"Journal of the American Chemical Society","topic":"Advanced Polymer Synthesis and Characterization","field":"Chemistry","cited_by":450,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University; Université de Sherbrooke","funders":"China Scholarship Council; Natural Sciences and Engineering Research Council of Canada; SFU Community Trust Endowment Fund; Canada Research Chairs; Simon Fraser University; Michael Smith Health Research BC","keywords":"Micelle; Copolymer; Chemistry; Dissociation (chemistry); Photochemistry; Ethylene oxide; Nanoparticle; Methacrylate; Visible spectrum; Infrared; Photodissociation; Chemical engineering; Nanotechnology; Optoelectronics; Materials science; Organic chemistry; Optics; Polymer; Aqueous solution","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":[0.0001021809,0.0002416107,0.0001554621,0.0001050965,0.00008916736,0.0001758168,0.000189614,0.0002440184,0.0006656836],"category_scores_gemma":[0.0001410031,0.0001276602,0.0001560524,0.00005631709,0.0001591606,0.0003037844,0.0001992694,0.000341378,0.0002893007],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002258718,"about_ca_system_score_gemma":0.0001314356,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002706814,"about_ca_topic_score_gemma":0.0004518647,"domain_scores_codex":[0.9999166,0.00001106198,0.000005185477,0.00002393826,0.00002498937,0.00001813884],"domain_scores_gemma":[0.9999309,0.00001387657,0.00002647971,0.000008107719,0.000008221664,0.00001251842],"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":[0.00001463704,0.000007522264,0.00002465094,0.0000117719,0.000001249088,0.00001829372,0.000009141616,0.00006283969,0.9985698,0.00009909857,0.00001497478,0.001166019],"study_design_scores_gemma":[0.000002989115,0.00002206886,0.0001001841,6.670252e-7,0.000001207356,0.00003194936,0.000001713634,0.0005021144,0.9988716,0.00001261969,0.000451542,0.000001261178],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9785933,0.001316597,0.01710307,0.0001277143,0.00002943559,0.00004299337,0.00005116478,0.0001993683,0.002536391],"genre_scores_gemma":[0.9861621,0.0005742856,0.009849721,0.00005935444,0.00001079938,0.00003191396,0.0000731189,0.00004531128,0.003193449],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0006656836,"threshold_uncertainty_score":0.002226949,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01630447928552987,"score_gpt":0.2353207774498249,"score_spread":0.2190162981642951,"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."}}