{"id":"W2738699253","doi":"10.1002/advs.201700252","title":"Photothermal Catalyst Engineering: Hydrogenation of Gaseous CO<sub>2</sub> with High Activity and Tailored Selectivity","year":2017,"lang":"en","type":"article","venue":"Advanced Science","topic":"Advanced Photocatalysis Techniques","field":"Energy","cited_by":128,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; Dalhousie University; York University; University of Toronto","funders":"Argonne National Laboratory; Basic Energy Sciences; Natural Sciences and Engineering Research Council of Canada; Office of Science; Government of Canada; U.S. Department of Energy; Ministero dello Sviluppo Economico; Canadian Light Source; University of Toronto","keywords":"Selectivity; Catalysis; Photothermal therapy; Chemical engineering; Materials science; Fischer–Tropsch process; Chemistry; Nanotechnology; Organic chemistry; Engineering","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":[0.00008709542,0.0002144892,0.0002154505,0.0001161703,0.000108432,0.0003446511,0.0002688694,0.0002311531,0.0004686145],"category_scores_gemma":[0.0001121885,0.0001431792,0.0001386463,0.0001017162,0.0002257885,0.0002695254,0.0001773371,0.000217852,0.0001936261],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004689236,"about_ca_system_score_gemma":0.0001519824,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006654245,"about_ca_topic_score_gemma":0.002169381,"domain_scores_codex":[0.9999024,0.000007884763,0.000005851696,0.00002763425,0.00003465351,0.00002157871],"domain_scores_gemma":[0.9999614,0.000008818329,0.00001014606,0.000005445015,0.000007888545,0.00000638228],"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":[0.00002553166,0.00001217272,0.00006817766,0.00003840425,0.000004073868,0.00001749276,0.000007910499,0.000285445,0.9968176,0.0002362323,0.00005133021,0.002435716],"study_design_scores_gemma":[0.000004297306,0.00002716499,0.0002478155,8.420712e-7,0.000004087747,0.00003823625,0.000005640116,0.002029216,0.9966552,0.00002622316,0.0009591784,0.000002186063],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9677131,0.001614906,0.02279176,0.0001708324,0.00005786363,0.00004539023,0.0001162818,0.0002363292,0.007253522],"genre_scores_gemma":[0.9906419,0.000358749,0.007641745,0.00003409861,0.000006692806,0.00001677814,0.00004397648,0.00002085295,0.001235109],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0006654245,"threshold_uncertainty_score":0.003402293,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006646947737906505,"score_gpt":0.2443722452912086,"score_spread":0.2377252975533021,"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."}}