{"id":"W2329456377","doi":"10.1021/ma3012976","title":"Covalent Capture of Self-Assembled Rosette Nanotubes","year":2012,"lang":"en","type":"article","venue":"Macromolecules","topic":"Supramolecular Self-Assembly in Materials","field":"Materials Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Institute for Nanotechnology; University of Alberta","funders":"Luonnontieteiden ja Tekniikan Tutkimuksen Toimikunta; University of Alberta","keywords":"Covalent bond; Differential scanning calorimetry; Surface modification; Materials science; Fourier transform infrared spectroscopy; Supramolecular chemistry; Polymer; Polymer chemistry; Chemical engineering; Chemistry; Molecule; Physical chemistry; Organic chemistry; Composite material; Physics","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":[0.0009345126,0.0003512569,0.0005171308,0.0001182309,0.0001193979,0.0001100098,0.0005962176,0.0001954811,0.0006272697],"category_scores_gemma":[0.0001203751,0.0003146282,0.0001600254,0.0002287073,0.0000543576,0.0003010902,0.0002591521,0.0001034882,0.0007232823],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008304069,"about_ca_system_score_gemma":0.00007316926,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001094561,"about_ca_topic_score_gemma":0.000006226372,"domain_scores_codex":[0.9972075,0.000373333,0.000590551,0.0003961261,0.0006060176,0.0008264218],"domain_scores_gemma":[0.998529,0.0001086219,0.0002838789,0.0007177388,0.0001496509,0.0002111201],"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":[0.00003065126,0.0002589851,0.002498731,0.0001202081,0.00003741918,0.00002300728,0.0007840971,0.00001040503,0.9933515,0.002108478,0.0007169543,0.00005954845],"study_design_scores_gemma":[0.0004294524,0.00006094043,0.003273274,0.00004407101,0.00008520864,0.0000714775,0.0001811862,0.00001277513,0.9930122,0.0001835265,0.002288121,0.0003578038],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9941818,0.001056474,0.0007712027,0.0001257137,0.001429222,0.0003433183,0.00004629848,0.0003070368,0.001738947],"genre_scores_gemma":[0.9875922,0.00002935643,0.01171839,0.0002991779,0.000183783,0.0000536747,0.00001413273,0.00006736397,0.00004197543],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01094718,"threshold_uncertainty_score":0.9999306,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01037662739844615,"score_gpt":0.2454529710223571,"score_spread":0.2350763436239109,"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."}}