{"id":"W4389723807","doi":"10.1109/neessc59976.2023.10349336","title":"Preface","year":2023,"lang":"en","type":"article","venue":"","topic":"Power Systems and Renewable Energy","field":"Energy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Battery (electricity); China; Summit; State (computer science); Computer science; Big data; Engineering; Library science; Power (physics); Engineering management; Political science; Geography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001748915,0.00111254,0.0008749915,0.002233733,0.003234152,0.004802395,0.001844916,0.002073764,0.5526989],"category_scores_gemma":[0.00921498,0.0003822003,0.0007355942,0.001813368,0.00079243,0.003934606,0.002994816,0.003270236,0.3838455],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002305832,"about_ca_system_score_gemma":0.003268378,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003616022,"about_ca_topic_score_gemma":0.004285523,"domain_scores_codex":[0.9985733,0.000207354,0.0001082037,0.0002922044,0.0006424657,0.0001764181],"domain_scores_gemma":[0.9959369,0.0005430563,0.0001411073,0.0003877312,0.002286243,0.0007048381],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003314639,0.00002043785,0.0001253027,0.0001064488,0.000002408244,0.00005998196,0.0001184891,0.00005053599,0.0001146253,0.005598353,0.9543508,0.03941948],"study_design_scores_gemma":[0.000003156468,0.00001208551,0.0001767713,0.00007452154,0.000001103794,0.00005814247,0.0001022709,0.00001928297,0.00004769401,0.001208128,0.9982933,0.000003586577],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.001775014,0.008865667,0.005485381,0.03200374,0.1105552,0.0006511805,0.01211681,0.002040356,0.8265067],"genre_scores_gemma":[0.007217609,0.004773313,0.002452,0.008191057,0.01238979,0.0003541521,0.01024777,0.0008660759,0.9535081],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.4473011,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01656720067440176,"score_gpt":0.2366656946478058,"score_spread":0.2200984939734041,"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."}}