{"id":"W2958608438","doi":"10.1103/physrevmaterials.3.075603","title":"Molecular simulation of silica gels: Formation, dilution, and drying","year":2019,"lang":"en","type":"article","venue":"Physical Review Materials","topic":"Mesoporous Materials and Catalysis","field":"Materials Science","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada; College of Natural Resources and Sciences, Humboldt State University; Compute Canada","keywords":"Materials science; Dilution; Silicon; Colloid; Chemical engineering; Composite material; Thermodynamics","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005965159,0.0001549467,0.0006305013,0.00002797856,0.00004136668,0.0000588304,0.0001433599,0.00002893649,0.001029616],"category_scores_gemma":[0.0001401854,0.0001217727,0.0000667209,0.0001093749,0.00004629883,0.0003415836,0.00009623114,0.00002144904,0.0003573576],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001652755,"about_ca_system_score_gemma":0.00001471002,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001857314,"about_ca_topic_score_gemma":2.233047e-7,"domain_scores_codex":[0.9985759,0.0001763021,0.0005487595,0.0002525239,0.0002659054,0.0001806024],"domain_scores_gemma":[0.9990413,0.00007409449,0.0003626403,0.0003462457,0.0001197787,0.00005599448],"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":[0.00001063184,0.00003225349,0.000009498677,0.002487325,0.000005451383,3.857317e-7,0.00006233851,0.0001555732,0.9943074,0.002439021,0.00002432662,0.0004657725],"study_design_scores_gemma":[0.0001393471,0.00003672353,0.0001552553,0.0006694524,0.00007418674,0.000001972654,0.000007082171,0.0002276375,0.995697,0.002178504,0.000670534,0.0001423618],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9962887,0.002433657,0.0002329081,0.0000957211,0.0001500312,0.0005034413,0.0000478622,0.00003740547,0.0002102893],"genre_scores_gemma":[0.9985543,0.0009791709,0.00008953431,0.0002075292,0.00006499051,0.00003385796,0.00004302332,0.00001496252,0.00001256694],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00226568,"threshold_uncertainty_score":0.9998836,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01082154321561984,"score_gpt":0.2865137986785553,"score_spread":0.2756922554629354,"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."}}