{"id":"W4402721765","doi":"10.23977/acss.2024.080602","title":"Application of Forewarning Based on CFL","year":2024,"lang":"en","type":"article","venue":"Advances in Computer Signals and Systems","topic":"Power Systems and Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Key Research and Development Program of China","keywords":"Environmental science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003467838,0.000689303,0.0004419702,0.001473451,0.0005126125,0.0005883076,0.0006979217,0.0005908898,0.002984967],"category_scores_gemma":[0.001771045,0.0001615634,0.0003487341,0.0006999235,0.000321891,0.001047044,0.0008547869,0.000499711,0.0005365579],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004339594,"about_ca_system_score_gemma":0.000770914,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005305165,"about_ca_topic_score_gemma":0.003040087,"domain_scores_codex":[0.9995474,0.00004655762,0.00002545348,0.000101265,0.0002090214,0.00007023892],"domain_scores_gemma":[0.9993905,0.0001346974,0.00007978585,0.00007122241,0.0002725188,0.00005134578],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0007372083,0.0001274756,0.01275341,0.0004130611,0.00005882262,0.001054552,0.0005744644,0.09561794,0.1130748,0.007981895,0.009925216,0.7576812],"study_design_scores_gemma":[0.00006380781,0.0003790131,0.009041378,0.00009154282,0.0000777191,0.0006773537,0.0001991908,0.9091625,0.06082493,0.004868549,0.01448846,0.0001255878],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.165238,0.001414545,0.7952656,0.0007358115,0.0005966073,0.0003044862,0.000636923,0.005982405,0.02982561],"genre_scores_gemma":[0.9301971,0.0003136356,0.06512155,0.0002028064,0.00009814555,0.00007486483,0.0003229291,0.00009286546,0.003576116],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005305165,"threshold_uncertainty_score":0.01054859,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007045565961982362,"score_gpt":0.2289613426765576,"score_spread":0.2219157767145753,"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."}}