{"id":"W3033777732","doi":"10.1002/anie.202007224","title":"Non‐Lithography Hydrodynamic Printing of Micro/Nanostructures on Curved Surfaces","year":2020,"lang":"en","type":"article","venue":"Angewandte Chemie International Edition","topic":"Nanofabrication and Lithography Techniques","field":"Engineering","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"K. C. Wong Education Foundation; National Key Research and Development Program of China; Beijing National Laboratory for Molecular Sciences; Youth Innovation Promotion Association of the Chinese Academy of Sciences; National Natural Science Foundation of China; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung","keywords":"Lithography; Nanotechnology; Materials science; Nanostructure; 3D printing; Optoelectronics; Composite material","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0001431086,0.0003439386,0.0002478302,0.0001961254,0.0001598241,0.0003214852,0.0004512527,0.0002844648,0.00190344],"category_scores_gemma":[0.0002791082,0.0003153699,0.0003836215,0.000160031,0.0003537472,0.0002805799,0.0004373171,0.0004924742,0.001099336],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002965378,"about_ca_system_score_gemma":0.0001947695,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003039994,"about_ca_topic_score_gemma":0.0006025461,"domain_scores_codex":[0.9997334,0.00002987287,0.00001778155,0.00005710096,0.0001264904,0.00003539931],"domain_scores_gemma":[0.9997707,0.00006354759,0.00004748079,0.00008016873,0.00002668798,0.00001144692],"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":[0.00001553233,0.0000119491,0.00006018173,0.0000607962,0.000005716143,0.00008310482,0.00001742616,0.0006480492,0.9928662,0.0009003959,0.0001717245,0.005158939],"study_design_scores_gemma":[0.000004636703,0.00003084664,0.000321259,0.000002621192,0.000002724694,0.0001229595,0.000005701388,0.003398811,0.9941574,0.0002047825,0.001742065,0.00000617548],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6166875,0.002655454,0.355843,0.0004158036,0.0003263211,0.0001712834,0.0005238385,0.00285614,0.02052065],"genre_scores_gemma":[0.8283383,0.001162612,0.1591415,0.0001555676,0.00003870505,0.00007750063,0.0003812414,0.0002756281,0.01042895],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00190344,"threshold_uncertainty_score":0.006367683,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00888248073272974,"score_gpt":0.2232002204308609,"score_spread":0.2143177396981312,"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."}}