{"id":"W2008923746","doi":"10.1021/la7034054","title":"Nanomechanical Fingerprints of Individual Blocks of a Diblock Copolymer Chain","year":2008,"lang":"en","type":"article","venue":"Langmuir","topic":"Force Microscopy Techniques and Applications","field":"Physics and Astronomy","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Office of Naval Research; Army Research Office; Division of Chemistry; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; National Science Foundation","keywords":"Copolymer; Polystyrene; Polymer; Materials science; Methyl methacrylate; Atomic force microscopy; Chain (unit); Polymer chemistry; Methacrylate; Plateau (mathematics); Molecular dynamics; Chemical physics; Nanotechnology; Composite material; Chemistry; Computational chemistry; 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":[],"consensus_categories":[],"category_scores_codex":[0.00004829937,0.00007397348,0.0001603991,0.00003751192,0.00004932149,0.000002578387,0.0001749452,0.00003411302,0.0003892834],"category_scores_gemma":[0.000001129138,0.00006805432,0.00007653664,0.0001286698,0.00007556732,0.00001694969,0.00007585268,0.00006828472,0.000008178276],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000035924,"about_ca_system_score_gemma":0.00002137112,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001300129,"about_ca_topic_score_gemma":6.433506e-7,"domain_scores_codex":[0.9994828,0.000008793259,0.0001865687,0.000110948,0.00009909469,0.0001117724],"domain_scores_gemma":[0.9996562,0.00001661049,0.0001011298,0.0001709714,0.00002745193,0.000027633],"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":[0.00003893135,0.001234286,0.07028484,0.00006669672,0.0002393458,0.000002657798,0.002657155,0.000008524111,0.6496816,0.2435953,0.02049169,0.01169887],"study_design_scores_gemma":[0.0003447904,0.00006904122,0.005286459,0.00002926246,0.00002390158,0.000002573494,0.0001267908,0.00007688906,0.9856408,0.001859809,0.006385277,0.0001544562],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9876314,0.00003975533,0.005709608,0.00006719214,0.00001634067,0.0001284285,0.0001501832,0.00002699399,0.006230144],"genre_scores_gemma":[0.9974097,0.000001561518,0.001801737,0.00002152524,0.00004644867,0.00002560726,0.0000305192,0.000009458381,0.0006534655],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3359591,"threshold_uncertainty_score":0.4262381,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01426629840149898,"score_gpt":0.2576513066469235,"score_spread":0.2433850082454245,"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."}}