{"id":"W2293319287","doi":"10.1038/srep19542","title":"Tuning and Freezing Disorder in Photonic Crystals using Percolation Lithography","year":2016,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Photonic Crystals and Applications","field":"Physics and Astronomy","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Multidisciplinary University Research Initiative; U.S. Air Force; Air Force Office of Scientific Research; Federal Railroad Administration; Natural Sciences and Engineering Research Council of Canada; U.S. Department of Defense","keywords":"Percolation (cognitive psychology); Capillary action; Materials science; Wetting; Photonic crystal; Photonics; Lithography; Porous medium; Microfluidics; Porosity; Nanotechnology; Evaporation; Chemical physics; Optoelectronics; Composite material; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001500031,0.00020476,0.0001330359,0.0002531272,0.0002661569,0.0003502576,0.0002878433,0.0001846715,0.0003207692],"category_scores_gemma":[0.0003575517,0.0002334577,0.0001757573,0.0001729938,0.0009577514,0.0004337092,0.0005838377,0.0004964927,0.0001071093],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000534776,"about_ca_system_score_gemma":0.0003583517,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008802392,"about_ca_topic_score_gemma":0.001721314,"domain_scores_codex":[0.9998456,0.00001987064,0.00001137264,0.00002873761,0.00005760189,0.00003682216],"domain_scores_gemma":[0.9997255,0.0001345167,0.00007085274,0.00003109944,0.00001555301,0.00002230391],"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":[0.00002175189,0.00001139599,0.0002394375,0.00003390461,0.000003591022,0.000057692,0.00005561186,0.002605972,0.9912526,0.002452242,0.00007251873,0.003193248],"study_design_scores_gemma":[0.00001239649,0.00003981748,0.0004711202,0.000006702944,0.000004499852,0.00009111167,0.00002559322,0.01557237,0.9809878,0.001268467,0.001502387,0.00001779349],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9401225,0.0007661287,0.05551525,0.0002235873,0.00003613871,0.00004667558,0.00008927593,0.0004540933,0.002746474],"genre_scores_gemma":[0.9833063,0.0004032287,0.01568105,0.0000492926,0.000006631031,0.00002870724,0.00003285675,0.00005894946,0.0004328363],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008802392,"threshold_uncertainty_score":0.003880084,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01273654435330144,"score_gpt":0.2564333390419793,"score_spread":0.2436967946886779,"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."}}