{"id":"W4413817563","doi":"10.1021/acselectrochem.5c00190","title":"Plasmonic Nanomaterials as Catalysts for CO<sub>2</sub> Electroreduction","year":2025,"lang":"en","type":"article","venue":"ACS electrochemistry.","topic":"CO2 Reduction Techniques and Catalysts","field":"Energy","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada; University of Ottawa","funders":"National Research Council Canada; Natural Sciences and Engineering Research Council of Canada","keywords":"Nanomaterials; Catalysis; Plasmon; Materials science; Nanotechnology; Chemistry; Optoelectronics; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001878004,0.0003136389,0.0003504921,0.0001257167,0.0002429505,0.00009123357,0.0003255458,0.0002877784,0.00003692339],"category_scores_gemma":[0.0001495525,0.0003443405,0.0001895982,0.0004228821,0.00006684502,0.0001210811,0.00004322354,0.0001674711,0.00004143139],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000350534,"about_ca_system_score_gemma":0.0003409143,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004919422,"about_ca_topic_score_gemma":0.00001788556,"domain_scores_codex":[0.9981372,0.00002438171,0.0004343983,0.0005924087,0.0001877493,0.0006238113],"domain_scores_gemma":[0.9989791,0.00005243591,0.0001714071,0.0005345333,0.0001747354,0.00008776916],"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":[0.000174287,0.00006552367,0.000002924883,0.00009483733,0.0001171763,0.000001701538,0.0000203845,0.000002619933,0.9573584,0.006807644,0.02590377,0.009450749],"study_design_scores_gemma":[0.0004418323,0.0001072318,0.000007702864,0.00002935317,0.00008601894,0.000101883,0.00002395925,0.0000058079,0.9356807,0.006299504,0.05692123,0.000294819],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9831673,0.0004969062,0.0004358415,0.0004949611,0.0003694256,0.0004054706,0.00001153949,0.0005686912,0.0140499],"genre_scores_gemma":[0.9926934,0.0002766017,0.0001117162,0.0001511917,0.000426357,0.0006063639,0.0006988132,0.00004670817,0.004988868],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03101745,"threshold_uncertainty_score":0.9999009,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005276934148374577,"score_gpt":0.254717492408313,"score_spread":0.2494405582599385,"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."}}