{"id":"W2921345083","doi":"10.1016/b978-0-12-814505-0.00004-7","title":"Organically Tailored Mesoporous Silicates Designed for Heavy Metal Sensing","year":2019,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Analytical Chemistry and Sensors","field":"Chemical Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Cape Breton University","funders":"","keywords":"Mesoporous material; Analyte; Materials science; Silicate; Nanotechnology; Adsorption; Metal ions in aqueous solution; Metal; Chemical engineering; Chemistry; Chromatography; Organic chemistry; Catalysis; Metallurgy","routes":{"ca_aff":true,"ca_fund":false,"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":[0.00008298801,0.0004208885,0.0001904734,0.0002047752,0.0000923444,0.0002677336,0.0003100522,0.0004282701,0.0008191473],"category_scores_gemma":[0.00008438614,0.0003216251,0.0001826724,0.0001635305,0.0001927414,0.0002907629,0.0002320472,0.0004186891,0.0007204524],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002706037,"about_ca_system_score_gemma":0.0001042604,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002924086,"about_ca_topic_score_gemma":0.0008340028,"domain_scores_codex":[0.9999442,0.000002724316,0.000003625467,0.0000127322,0.00002792982,0.000008809353],"domain_scores_gemma":[0.9999734,0.000006189379,0.000006846728,0.000002839434,0.000006905627,0.000003824579],"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":[0.00001195996,0.000007509846,0.00002229448,0.00007329787,0.000003780584,0.0000235099,0.00001004017,0.000165584,0.9943094,0.0003176338,0.0001424209,0.004912584],"study_design_scores_gemma":[0.000007234961,0.00007100754,0.0004381428,0.000009482555,0.00001027703,0.000108923,0.000008815167,0.001325013,0.984619,0.0001748114,0.01321796,0.000009346953],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.840316,0.02550588,0.09060054,0.0003721062,0.0009339038,0.0001854988,0.0008802702,0.001527025,0.03967884],"genre_scores_gemma":[0.860796,0.0141475,0.05657982,0.0005071429,0.0002062021,0.0001281391,0.001014819,0.0003005639,0.06631988],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.0008191473,"threshold_uncertainty_score":0.002740324,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01657193521928225,"score_gpt":0.2279821991701474,"score_spread":0.2114102639508651,"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."}}