{"id":"W4233312408","doi":"10.1002/cjce.22874","title":"Modified and systematic synthesis of zinc oxide‐silica composite nanoparticles with optimum surface area as a proper H<sub>2</sub>S sorbent","year":2017,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Industrial Gas Emission Control","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Sorbent; Zinc; Nanoparticle; Composite number; Materials science; Chemical engineering; Oxide; Nanotechnology; Composite material; Chemistry; Adsorption; Metallurgy; Engineering; Organic chemistry","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001235294,0.0004163746,0.0002864256,0.0002311983,0.0001788367,0.0002023801,0.0002609372,0.0002597195,0.0004727638],"category_scores_gemma":[0.0001564511,0.000205153,0.0002761721,0.0001822865,0.0002540878,0.0001990106,0.0002609787,0.000323841,0.0003171355],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003695902,"about_ca_system_score_gemma":0.000326906,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001014911,"about_ca_topic_score_gemma":0.003278751,"domain_scores_codex":[0.9998869,0.000009487591,0.000009361653,0.00003487936,0.00004108942,0.00001818135],"domain_scores_gemma":[0.9999346,0.000007458723,0.00001843784,0.000009830241,0.00002238045,0.000007252361],"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":[0.00002397322,0.00001007425,0.00007148247,0.0000763782,0.000005913737,0.00002141486,0.00001222754,0.000159348,0.9967945,0.0001319731,0.00005908334,0.002633511],"study_design_scores_gemma":[0.000005567636,0.00003967992,0.0003517298,0.000002490072,0.00001015433,0.0000372217,0.000006654297,0.0006122683,0.9975677,0.00003298713,0.001329397,0.000004237375],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9444686,0.004120576,0.04030496,0.0002035471,0.0002073674,0.0003835716,0.0004142196,0.0004941176,0.009402965],"genre_scores_gemma":[0.9632948,0.001304241,0.0311255,0.00007026433,0.00001688145,0.000110604,0.0001947332,0.00005752292,0.003825481],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001014911,"threshold_uncertainty_score":0.002681613,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01150037094380353,"score_gpt":0.1786472740650343,"score_spread":0.1671469031212307,"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."}}