{"id":"W2914425145","doi":"10.1021/jacs.9b00144","title":"C<sub>3</sub>N<sub>5</sub>: A Low Bandgap Semiconductor Containing an Azo-Linked Carbon Nitride Framework for Photocatalytic, Photovoltaic and Adsorbent Applications","year":2019,"lang":"en","type":"article","venue":"Journal of the American Chemical Society","topic":"Advanced Photocatalysis Techniques","field":"Energy","cited_by":820,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Institute for Nanotechnology; University of Alberta","funders":"National Research Council Canada; Canada First Research Excellence Fund; University of Alberta; Alberta Innovates; Alberta Innovates - Technology Futures; Natural Sciences and Engineering Research Council of Canada; CMC Microsystems","keywords":"Chemistry; Carbon nitride; Band gap; Graphitic carbon nitride; Photocatalysis; X-ray photoelectron spectroscopy; Photochemistry; Chemical engineering; Optoelectronics; Materials science; Organic chemistry","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":[0.0000481081,0.0002498959,0.00009732725,0.0001203745,0.0001310272,0.0001958199,0.0002600126,0.0002645941,0.0005653775],"category_scores_gemma":[0.00004881861,0.00005929618,0.000113725,0.0001172523,0.0001352908,0.0001242928,0.0001238033,0.0001669792,0.0001761862],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003875005,"about_ca_system_score_gemma":0.0001837891,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001855613,"about_ca_topic_score_gemma":0.004415839,"domain_scores_codex":[0.9999465,0.000003902847,0.000002408527,0.00001121331,0.00002384881,0.00001222678],"domain_scores_gemma":[0.9999677,0.000003104674,0.000009515136,0.000002139114,0.000009437785,0.000008129193],"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":[0.00002756328,0.000006599604,0.0001214744,0.00005175001,0.000003395951,0.00004269846,0.000004691971,0.0001122332,0.9978122,0.0001194885,0.00005969281,0.001638083],"study_design_scores_gemma":[0.000002309458,0.00008835887,0.002225955,0.000003544867,0.000007618402,0.0001991433,0.000009455503,0.001482541,0.9938343,0.00002765281,0.002115523,0.000003708666],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9888018,0.001392919,0.005508812,0.00008153348,0.000031468,0.00002538932,0.0002090504,0.0001284818,0.003820598],"genre_scores_gemma":[0.9916782,0.000361996,0.00498672,0.00004270014,0.000005297654,0.00001230451,0.0002101867,0.00001489994,0.002687657],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001855613,"threshold_uncertainty_score":0.003689647,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0108986996057536,"score_gpt":0.2674594689407445,"score_spread":0.2565607693349909,"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."}}