{"id":"W3175674495","doi":"10.1016/j.mtener.2021.100806","title":"Porous carbonized cotton loaded with Zn–Cu–M(M=O, S) nanocomposites for electrochemical energy storage and oxygen evolution reaction","year":2021,"lang":"en","type":"article","venue":"Materials Today Energy","topic":"Supercapacitor Materials and Fabrication","field":"Materials Science","cited_by":14,"is_retracted":false,"has_abstract":false,"ca_institutions":"Ministry of Education and Child Care; University of Calgary","funders":"China Scholarship Council; Donghua University; National Natural Science Foundation of China","keywords":"Materials science; Carbonization; Nanocomposite; Porosity; Energy storage; Chemical engineering; Electrochemistry; Oxygen evolution; Electrochemical energy storage; Oxygen; Supercapacitor; Composite material; Electrode; Scanning electron microscope; 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003002185,0.0003275368,0.000521678,0.00008605971,0.0002233655,0.0002791455,0.0001550669,0.0002325246,0.000181119],"category_scores_gemma":[0.00005078065,0.0002897775,0.00004880313,0.0001577481,0.0001000045,0.0003089351,0.00007196673,0.0000377098,0.000006625497],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00020568,"about_ca_system_score_gemma":0.0001160132,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009889182,"about_ca_topic_score_gemma":0.00007812293,"domain_scores_codex":[0.997824,0.0002222163,0.0004811503,0.0007017988,0.0002824408,0.0004883596],"domain_scores_gemma":[0.9989036,0.00009147664,0.0002245078,0.0003872239,0.0002660257,0.0001271823],"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":[0.0006456727,0.00008230229,0.0000192187,0.0000446698,0.00002572411,0.000009745191,0.00009310692,0.00000350101,0.9918823,0.00676821,0.000251503,0.0001740672],"study_design_scores_gemma":[0.001099021,0.0001863829,0.000459174,0.00004611433,0.00007311074,0.0001393724,0.0000738884,0.00005018678,0.9938729,0.0008705453,0.002742715,0.0003865485],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9885505,0.0006426444,0.009123242,0.0001465268,0.0009313137,0.0001488716,0.00006771734,0.0002327084,0.0001564987],"genre_scores_gemma":[0.9960329,0.00008833551,0.001975005,0.0001685083,0.0006628094,0.0002621297,0.0004734117,0.00006291182,0.0002739766],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007482435,"threshold_uncertainty_score":0.9999554,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006920783155977693,"score_gpt":0.1993476014879017,"score_spread":0.192426818331924,"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."}}