{"id":"W4293213436","doi":"10.56354/jendelainovasi.v5i2.123","title":"ANALISIS VOLATILITAS HARGA DAGING SAPI MURNI DI PROVINSI JAWA TENGAH DENGAN PENDEKATAN ARCH GARCH","year":2022,"lang":"en","type":"article","venue":"Jurnal Jendela Inovasi Daerah","topic":"Livestock Farming and Management","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Encana (Canada)","funders":"","keywords":"Volatility (finance); Autoregressive conditional heteroskedasticity; Commodity; Arch; Economics; Java; Econometrics; Geography; Computer science; Finance","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.001039393,0.0003346751,0.0003440841,0.0001031407,0.001641742,0.000213438,0.0009312672,0.00006957303,0.0008744738],"category_scores_gemma":[0.00007539527,0.0001640941,0.0002474119,0.0008575,0.00008884447,0.0002959339,0.0009830442,0.0009268773,0.00002817182],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002262983,"about_ca_system_score_gemma":0.00005140068,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001364205,"about_ca_topic_score_gemma":0.0005004075,"domain_scores_codex":[0.996556,0.0003634875,0.0005344357,0.0007407602,0.001044423,0.0007609276],"domain_scores_gemma":[0.9989412,0.0002442871,0.0002075216,0.0002360405,0.0001163217,0.0002546075],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003371825,0.001517649,0.4362969,0.0001350412,0.0004100227,0.0005726228,0.003587241,0.0005913594,0.1274437,0.008840999,0.02173094,0.3985364],"study_design_scores_gemma":[0.0008346423,0.001362745,0.777482,0.00005169151,0.0001460609,0.0002561051,0.01260267,0.001381617,0.001448723,0.0005701716,0.2027905,0.001073129],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9892383,0.000363638,0.00002657049,0.001901975,0.0004270965,0.0004742803,0.0001363328,0.0001870232,0.007244775],"genre_scores_gemma":[0.9969639,0.00003367073,0.000137837,0.0007715066,0.0004899639,0.0001154555,0.0002097287,0.000006468835,0.001271461],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3974632,"threshold_uncertainty_score":0.999658,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02224610892868635,"score_gpt":0.2175999643774138,"score_spread":0.1953538554487275,"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."}}