{"id":"W3114260101","doi":"","title":"ANALISA PEREKONOMIAN INDONESIA TRIWULAN III AKIBAT COVID19","year":2020,"lang":"en","type":"article","venue":"","topic":"SMEs Development and Digital Marketing","field":"Social Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Quarter (Canadian coin); Indonesian; Government (linguistics); Coronavirus disease 2019 (COVID-19); Indonesian government; Economic growth; Business; Economic recovery; Pandemic; Economics; Development economics; Economic policy; Geography; Macroeconomics","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":[],"consensus_categories":[],"category_scores_codex":[0.0009051122,0.0002959566,0.0003026763,0.002084988,0.0008183312,0.001765718,0.0002664347,0.0002331452,0.01084402],"category_scores_gemma":[0.001589899,0.0001431726,0.0002201193,0.00258318,0.000355463,0.0009562447,0.000775278,0.0005178349,0.002216002],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001277541,"about_ca_system_score_gemma":0.002115195,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007901252,"about_ca_topic_score_gemma":0.01271797,"domain_scores_codex":[0.9993076,0.0001216428,0.00008339165,0.00009196206,0.0002805004,0.0001148845],"domain_scores_gemma":[0.9990157,0.0003210972,0.0001414929,0.00004449369,0.0003871919,0.00009000512],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0002698714,0.0004252786,0.4168624,0.002600742,0.00008589531,0.003907486,0.06830817,0.0006485587,0.005653124,0.014214,0.03658491,0.4504396],"study_design_scores_gemma":[0.00000861849,0.0001277941,0.5789441,0.001080239,0.00005664947,0.001331646,0.2402657,0.001090987,0.002356406,0.0009691786,0.1737252,0.00004342559],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.834948,0.001919727,0.002127245,0.001499704,0.0001960019,0.0003065484,0.003007193,0.00009733938,0.1558983],"genre_scores_gemma":[0.9677371,0.001855003,0.00259631,0.0002068539,0.00002776688,0.0002553663,0.001937722,0.00003393126,0.02534993],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01084402,"threshold_uncertainty_score":0.03627688,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04787138350520486,"score_gpt":0.2878243778816328,"score_spread":0.239952994376428,"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."}}