{"id":"W4200561538","doi":"10.1021/acs.macromol.1c02241","title":"Probing the Analogy between Living Crystallization-Driven Self-Assembly and Living Covalent Polymerizations: Length-Independent Growth Behavior for 1D Block Copolymer Nanofibers","year":2021,"lang":"en","type":"article","venue":"Macromolecules","topic":"Advanced Polymer Synthesis and Characterization","field":"Chemistry","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; University of Victoria","funders":"Japan Society for the Promotion of Science; Natural Sciences and Engineering Research Council of Canada; Government of Canada","keywords":"Copolymer; Dispersity; Micelle; Crystallization; Transmission electron microscopy; Materials science; Chemical physics; Fiber; Nanofiber; Chemical engineering; Degree of polymerization; Amphiphile; Monomer; Growth rate; Polymer chemistry; Crystallography; Polymerization; Polymer; Chemistry; Nanotechnology; Composite material; Physical 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001103572,0.0003132292,0.0003217676,0.00006878721,0.0006121976,0.0002169566,0.0002391311,0.0001659783,0.0001461507],"category_scores_gemma":[0.0001220797,0.0002928855,0.0001259613,0.0002158647,0.00007447333,0.0001949233,0.0002055085,0.0001368608,0.000002763392],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007286918,"about_ca_system_score_gemma":0.0001220147,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003744034,"about_ca_topic_score_gemma":0.000023566,"domain_scores_codex":[0.9981525,0.00009676106,0.0004768972,0.0005624999,0.0002778912,0.0004334832],"domain_scores_gemma":[0.9985788,0.0004912947,0.0002883257,0.0003506266,0.0001735433,0.0001173709],"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":[0.000005449422,0.0001409292,0.02418755,0.0002196922,0.000194234,0.00001518531,0.001908059,0.00001783162,0.9690817,0.0007627819,0.00001517556,0.003451427],"study_design_scores_gemma":[0.0003799076,0.00003896087,0.01192904,0.0005051178,0.0005090653,0.00008925591,0.001672432,0.000959828,0.9825147,0.00004412879,0.0007016016,0.0006558965],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9615062,0.001497295,0.03518772,0.0004903469,0.0001422455,0.0003551433,0.0001875682,0.0001993214,0.0004341761],"genre_scores_gemma":[0.99655,0.0003091771,0.001775513,0.0001506027,0.0002764474,0.0002696969,0.0001783422,0.00009126386,0.0003990079],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03504376,"threshold_uncertainty_score":0.9999523,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01086899265280011,"score_gpt":0.2367627755767845,"score_spread":0.2258937829239844,"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."}}