{"id":"W3016478527","doi":"10.1039/d0ta02395g","title":"Metal–organic framework derived copper catalysts for CO<sub>2</sub> to ethylene conversion","year":2020,"lang":"en","type":"article","venue":"Journal of Materials Chemistry A","topic":"CO2 Reduction Techniques and Catalysts","field":"Energy","cited_by":125,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Recruitment Program of Global Experts; National Natural Science Foundation of China","keywords":"Copper; Catalysis; Ethylene; Metal; Materials science; Inorganic chemistry; Chemistry; Crystallography; Metallurgy; Organic chemistry","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003025376,0.0002070711,0.0005170825,0.00003338264,0.00007250447,0.00006996605,0.0003110691,0.0002272633,0.0004743734],"category_scores_gemma":[0.0003879224,0.0001905727,0.0002024676,0.0001470582,0.00003304286,0.0001244037,0.00007570531,0.0001682541,0.00005540015],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009543481,"about_ca_system_score_gemma":0.00009067031,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005528309,"about_ca_topic_score_gemma":3.137208e-7,"domain_scores_codex":[0.9985991,0.00003618485,0.0006383135,0.0002247711,0.0002691557,0.0002325211],"domain_scores_gemma":[0.9987042,0.00005899951,0.0004689017,0.0002141175,0.0002488049,0.00030496],"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":[0.0004807766,0.00003911521,0.000001791075,0.0002253086,0.000108829,0.00001878401,0.00021359,0.00001274045,0.9794747,0.00001297864,0.01900635,0.0004050323],"study_design_scores_gemma":[0.0004942178,0.0001330778,0.00001117157,0.0001010653,0.00010879,0.0001322871,0.0001454612,0.000001209472,0.9832525,0.0001800564,0.01523656,0.0002035489],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9955477,0.0001175759,0.001076712,0.002521068,0.0003508912,0.0001488496,0.00004936984,0.00006292533,0.0001249774],"genre_scores_gemma":[0.9965611,0.0001008296,0.001360667,0.0006894549,0.001137924,0.00001548027,0.00004593851,0.00004454166,0.00004406172],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003777845,"threshold_uncertainty_score":0.777133,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01526632238901621,"score_gpt":0.2518657578875891,"score_spread":0.2365994354985729,"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."}}