{"id":"W4385725543","doi":"10.1002/adma.202302826","title":"Liquid‐Templating Aerogels","year":2023,"lang":"en","type":"article","venue":"Advanced Materials","topic":"Electromagnetic wave absorption materials","field":"Materials Science","cited_by":51,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; Okanagan University College; University of British Columbia, Okanagan Campus; University of British Columbia","funders":"Basic Energy Sciences; Canada Research Chairs; Office of Science; Natural Sciences and Engineering Research Council of Canada; Canada Excellence Research Chairs, Government of Canada; U.S. Department of Energy","keywords":"Materials science; Aerogel; Microscale chemistry; Fabrication; Nanotechnology; Porosity; Template; Nanoengineering; Electromagnetic shielding; Nanoparticle; Nanoscopic scale; Composite material","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001498903,0.0002877112,0.0004686226,0.0001589905,0.0002234538,0.0002067657,0.0003967654,0.0001154241,0.006735783],"category_scores_gemma":[0.000465893,0.0002750927,0.00005389351,0.0004052835,0.0000957141,0.0004540956,0.0002170033,0.00005294599,0.01277062],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007483598,"about_ca_system_score_gemma":0.00005832308,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002251212,"about_ca_topic_score_gemma":0.000003882159,"domain_scores_codex":[0.9971842,0.00020599,0.0007094965,0.0005690236,0.0005093927,0.0008219568],"domain_scores_gemma":[0.9987104,0.0001755268,0.0002744311,0.0005575109,0.0001529947,0.0001291435],"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":[0.0001188514,0.00001342045,0.00000368378,0.00004798669,0.000004485505,0.00002301729,0.00008642535,0.0001115556,0.9964612,0.001702326,0.001220061,0.0002069454],"study_design_scores_gemma":[0.0004584389,0.0002579405,0.0003055974,0.00005183241,0.00001089295,0.00001773792,0.00004836512,0.000002946099,0.9917153,0.002850604,0.003959663,0.0003206525],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9941413,0.00003951466,0.00009393534,0.0002729921,0.002231857,0.0004178423,0.0001195336,0.001389876,0.001293154],"genre_scores_gemma":[0.9932656,0.00004770336,0.004510805,0.0002442689,0.0003608209,0.000187354,0.0000699611,0.00007656066,0.001236968],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006034839,"threshold_uncertainty_score":0.9999701,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01643430382467326,"score_gpt":0.2716872237784388,"score_spread":0.2552529199537656,"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."}}