{"id":"W4366713939","doi":"10.1016/j.est.2023.107376","title":"Modeling of capacitance for carbon-based supercapacitors using Super Learner algorithm","year":2023,"lang":"en","type":"article","venue":"Journal of Energy Storage","topic":"Supercapacitor Materials and Fabrication","field":"Materials Science","cited_by":20,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"Shahrood University of Technology","keywords":"Capacitance; Supercapacitor; Materials science; Carbon fibers; Microporous material; Electrode; Capacitor; Analytical Chemistry (journal); Voltage; Chemistry; Composite material; Electrical engineering; Engineering; Chromatography","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002898791,0.0003455698,0.0006290597,0.000338196,0.0005234455,0.0006223221,0.001240112,0.00129221,0.00345142],"category_scores_gemma":[0.0009560379,0.0002781832,0.0004580308,0.0006022889,0.0003811433,0.0008807921,0.0003574203,0.0006262542,0.0003515701],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009093652,"about_ca_system_score_gemma":0.001173707,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01597141,"about_ca_topic_score_gemma":0.01549187,"domain_scores_codex":[0.9999045,0.00001892298,0.000003729351,0.00001964571,0.00003602365,0.00001717124],"domain_scores_gemma":[0.999649,0.000185578,0.00002236034,0.00001850263,0.0001030747,0.00002139244],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001320769,0.00001325392,0.0001671633,0.00002053728,0.000007277005,0.00003538251,0.000009718347,0.9931091,0.0006578431,0.002891314,0.0002980107,0.002777246],"study_design_scores_gemma":[6.367093e-7,0.000001132714,0.00001540157,8.066658e-7,4.546825e-7,0.000002035563,9.023645e-7,0.9996578,0.00007102743,0.0001780932,0.00007109669,6.035497e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1419442,0.001244446,0.8183897,0.0008250021,0.0001470629,0.0001215104,0.0004470271,0.0006511436,0.03622997],"genre_scores_gemma":[0.949529,0.0003828361,0.03938617,0.0001259102,0.00003650962,0.0001039247,0.0001642646,0.00009846531,0.01017289],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01597141,"threshold_uncertainty_score":0.03175694,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0378224777778965,"score_gpt":0.2614155239991471,"score_spread":0.2235930462212506,"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."}}