{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008213796,0.000263867,0.0001295634,0.0001975217,0.0001089968,0.0002181903,0.0001560355,0.0001966551,0.001108458],"category_scores_gemma":[0.0001077457,0.0001008284,0.000210829,0.0001163587,0.0001983008,0.0002382935,0.0002399537,0.00037304,0.0004384025],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000248846,"about_ca_system_score_gemma":0.0001179577,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002777477,"about_ca_topic_score_gemma":0.0005454666,"domain_scores_codex":[0.9999181,0.000008525523,0.000004668425,0.00002126588,0.00003076909,0.00001669721],"domain_scores_gemma":[0.9999323,0.00001508486,0.00002560662,0.000006743664,0.00001076673,0.000009525258],"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":[0.00000765911,0.000004238933,0.00002528694,0.00004397697,0.000003604442,0.00003797236,0.000009428191,0.0002044784,0.9980447,0.0002526388,0.00007381709,0.001292289],"study_design_scores_gemma":[0.000002485611,0.0000352506,0.0001613552,0.000003837755,0.000003602679,0.00004720881,0.000004760742,0.0007832014,0.9947154,0.00007442729,0.004164674,0.000003925824],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9321347,0.004179966,0.04586482,0.0003256038,0.0001907188,0.00007469481,0.0008214527,0.0009960507,0.01541201],"genre_scores_gemma":[0.9839137,0.001106493,0.01060757,0.0001004112,0.00002462452,0.00002480029,0.0002835037,0.00008709661,0.003851752],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001108458,"threshold_uncertainty_score":0.003708184,"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."}}