{"id":"W2006053869","doi":"10.1021/la703406d","title":"Chemical Imaging of the Surface of Self-Assembled Polystyrene-<i>b</i>-Poly(methyl methacrylate) Diblock Copolymer Films Using Apertureless Near-Field IR Microscopy","year":2008,"lang":"en","type":"article","venue":"Langmuir","topic":"Near-Field Optical Microscopy","field":"Engineering","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"National Institute of Biomedical Imaging and Bioengineering; Division of Chemistry; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; National Institutes of Health","keywords":"Materials science; Polystyrene; Methyl methacrylate; Microscopy; Copolymer; Analytical Chemistry (journal); Poly(methyl methacrylate); Nanoscopic scale; Scattering; Thin film; Optics; Nanotechnology; Polymer; Chemistry; Composite material; Organic 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":[0.00009167111,0.0001945206,0.0001066808,0.0001887454,0.00009854146,0.0001313562,0.0001569081,0.0001915531,0.0008411879],"category_scores_gemma":[0.0001526552,0.000120019,0.00007619956,0.00009555495,0.0001424376,0.0002203402,0.00009597631,0.0002208221,0.0001761244],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001527222,"about_ca_system_score_gemma":0.00007548185,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003159669,"about_ca_topic_score_gemma":0.0003550806,"domain_scores_codex":[0.9999382,0.000009040939,0.000002391258,0.00001293263,0.00002713341,0.00001023707],"domain_scores_gemma":[0.999904,0.00002646239,0.00002269916,0.000006416639,0.00002400932,0.00001645442],"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":[0.000008073587,0.000002469129,0.00002748751,0.000006411027,4.571408e-7,0.000004678029,0.000002758484,0.00001394605,0.9996729,0.00001226903,0.000004432627,0.0002441471],"study_design_scores_gemma":[0.000005595837,0.00007366867,0.002849576,0.000002496842,0.000003975535,0.00007483656,0.00001396149,0.001391356,0.995265,0.00002327571,0.0002936157,0.000002671587],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9937669,0.0004494525,0.004439846,0.00003846814,0.00001074339,0.000009771145,0.00007239749,0.0000454849,0.001166858],"genre_scores_gemma":[0.9868336,0.0005383611,0.01072215,0.00003871305,0.00001165766,0.00001594303,0.000103603,0.00001610562,0.001719778],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008411879,"threshold_uncertainty_score":0.002814114,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007703467400650136,"score_gpt":0.2328259453319343,"score_spread":0.2251224779312842,"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."}}