{"id":"W4285728040","doi":"10.1038/s41467-022-31644-2","title":"Spongy all-in-liquid materials by in-situ formation of emulsions at oil-water interfaces","year":2022,"lang":"en","type":"article","venue":"Nature Communications","topic":"Innovative Microfluidic and Catalytic Techniques Innovation","field":"Engineering","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Alberta Innovates; Natural Sciences and Engineering Research Council of Canada; Government of Canada; Canada First Research Excellence Fund; University of Calgary","keywords":"Emulsion; Materials science; Drop (telecommunication); Nanoparticle; Microfluidics; Nanotechnology; Tube (container); Chemical engineering; Composite material; Computer science","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":[0.0001250528,0.0003517961,0.0001353415,0.0002111086,0.0001085054,0.0003195632,0.0002088421,0.0001901985,0.000707468],"category_scores_gemma":[0.000160296,0.0002330636,0.0001886776,0.0001160479,0.0002607778,0.0002489722,0.0002851969,0.0003444428,0.0002565802],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001597812,"about_ca_system_score_gemma":0.0001049901,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001571561,"about_ca_topic_score_gemma":0.0004782646,"domain_scores_codex":[0.999916,0.000008388495,0.000007384037,0.00002078035,0.00002953007,0.00001793918],"domain_scores_gemma":[0.999878,0.00002589876,0.00005189366,0.00001810331,0.00001072482,0.00001529839],"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":[0.000007391761,0.000006594707,0.0000510732,0.00001791629,0.000002835464,0.00005409277,0.00001683101,0.0001802704,0.9984915,0.0001125142,0.00002190401,0.001036921],"study_design_scores_gemma":[0.000002526911,0.00002343297,0.0002283937,0.000001446797,0.000003143571,0.00003763412,0.000004253613,0.0009513967,0.9981542,0.00003309933,0.0005588284,0.000001694715],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.947006,0.0005237358,0.04694768,0.00008281259,0.00004923621,0.00005291506,0.0001579167,0.0005792374,0.004600461],"genre_scores_gemma":[0.9822526,0.0002892131,0.01541472,0.00004532955,0.000009184313,0.00002613594,0.0001003847,0.00007744363,0.001784929],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.000707468,"threshold_uncertainty_score":0.002366722,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01866895508571231,"score_gpt":0.279414778153134,"score_spread":0.2607458230674217,"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."}}