{"id":"W4409270643","doi":"10.1002/adma.202419893","title":"Polymer Microarray with Tailored Morphologies through Condensed Droplet Polymerization for High‐Resolution Optical Imaging Applications","year":2025,"lang":"en","type":"article","venue":"Advanced Materials","topic":"Nanofabrication and Lithography Techniques","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Division of Civil, Mechanical and Manufacturing Innovation; Division of Materials Research; Natural Sciences and Engineering Research Council of Canada; National Institutes of Health; National Science Foundation","keywords":"Materials science; Polymerization; Nanotechnology; Polymer; Optical microscope; Microscopy; Lithography; Optics; Optoelectronics; Scanning electron microscope","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001223987,0.0002649359,0.0001767109,0.0001658385,0.00009974762,0.0002931813,0.0002547974,0.0002997866,0.001338884],"category_scores_gemma":[0.0001704243,0.0002281335,0.0001632056,0.0001584142,0.000169711,0.0004809498,0.0002292052,0.0004073566,0.000577617],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002709494,"about_ca_system_score_gemma":0.0001628008,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001456492,"about_ca_topic_score_gemma":0.0003602525,"domain_scores_codex":[0.999909,0.0000107921,0.000006371352,0.00002642152,0.00003463636,0.00001271112],"domain_scores_gemma":[0.9999244,0.00002126056,0.00002538617,0.00001079444,0.000008650813,0.000009427464],"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":[0.000007098635,0.000006215571,0.00001535474,0.00001366738,0.000001161436,0.00001141547,0.000005790058,0.0001031929,0.998163,0.0001545311,0.00003688226,0.001481505],"study_design_scores_gemma":[0.0000111096,0.00006363913,0.000284561,0.000001905811,0.000003995829,0.0000554619,0.000005617095,0.004029003,0.9927614,0.00006990205,0.002707969,0.000005466298],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8636299,0.002559126,0.1240137,0.0006085926,0.0001658361,0.000220389,0.0005616314,0.0009868018,0.007253925],"genre_scores_gemma":[0.8912981,0.001694331,0.1007982,0.0001980063,0.00004728342,0.0001615759,0.0003723167,0.000112248,0.005317985],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001338884,"threshold_uncertainty_score":0.004479051,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004452653001660549,"score_gpt":0.2333977911984382,"score_spread":0.2289451381967776,"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."}}