{"id":"W2766539155","doi":"10.1002/ppsc.201700297","title":"An In Situ Polymerization‐Encapsulation Approach to Prepare TiO<sub>2</sub>–Graphite Carbon–Au Photocatalysts for Efficient Photocatalysis","year":2017,"lang":"en","type":"article","venue":"Particle & Particle Systems Characterization","topic":"Advanced Photocatalysis Techniques","field":"Energy","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke; Hydro-Québec; Institut National de la Recherche Scientifique","funders":"Fonds Québécois de la Recherche sur la Nature et les Technologies; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Photocatalysis; Photodegradation; Materials science; Visible spectrum; Graphite; Catalysis; Chemical engineering; Nanoparticle; Polymerization; Carbon fibers; Irradiation; Nanotechnology; Photochemistry; Chemistry; Organic chemistry; Polymer; Optoelectronics; Composite material; Composite number","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":[0.000103671,0.0004054211,0.0002170505,0.000164443,0.0001068126,0.0002086498,0.0002130986,0.0002966868,0.0004504512],"category_scores_gemma":[0.0001234764,0.0002427475,0.0002315252,0.00009885807,0.0001481619,0.0001758537,0.0001799372,0.0003643375,0.0001937565],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002063861,"about_ca_system_score_gemma":0.0001219034,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002530084,"about_ca_topic_score_gemma":0.0007961509,"domain_scores_codex":[0.9999155,0.00001448118,0.000006809631,0.00001939878,0.00002604724,0.00001771532],"domain_scores_gemma":[0.9999335,0.00001311236,0.00002562556,0.0000111083,0.000008428265,0.000008195829],"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":[0.000006674113,0.00000586432,0.00001605755,0.00001331849,0.000002704299,0.00001001681,0.00000410199,0.00007060353,0.999332,0.00002720052,0.000006931116,0.0005045559],"study_design_scores_gemma":[0.000002223481,0.00003191503,0.000235699,7.85271e-7,0.000004789257,0.0000292952,0.000001634666,0.0005328009,0.9987351,0.000006179587,0.0004178396,0.000001730559],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9668275,0.001056401,0.02998026,0.00008875118,0.00004320885,0.00005838223,0.00008331448,0.000219629,0.001642609],"genre_scores_gemma":[0.9830852,0.0003785191,0.01492588,0.00002746725,0.000008752661,0.00002648667,0.00006201375,0.00002791468,0.001457795],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0004504512,"threshold_uncertainty_score":0.001506925,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01711076778956977,"score_gpt":0.2719127458646846,"score_spread":0.2548019780751148,"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."}}