{"id":"W2910455147","doi":"10.26858/ja.v5i2.7886","title":"Analisis Potensi Sektor Unggulan dan Pemetaan Kemiskinan Masyarakat di Wilayah Maminasata Sulawesi Selatan","year":2019,"lang":"en","type":"article","venue":"Jurnal Ad ministrare","topic":"Economic Growth and Fiscal Policies","field":"Economics, Econometrics and Finance","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"WiLAN (Canada)","funders":"","keywords":"Geography; Poverty; Socioeconomics; Typology; Lagging; Economic base analysis; Agricultural economics; Economic growth; Economics; Mathematics; Statistics; Archaeology","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":[0.0006982886,0.0002933141,0.0002929343,0.001483404,0.0004520835,0.001275974,0.0002755769,0.000197315,0.005059139],"category_scores_gemma":[0.001339371,0.0001503992,0.0002477033,0.00202158,0.0004182734,0.0008744819,0.000740933,0.0002778505,0.0007202296],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007876765,"about_ca_system_score_gemma":0.0006752595,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008579002,"about_ca_topic_score_gemma":0.01863354,"domain_scores_codex":[0.9996569,0.00006424301,0.00003797255,0.00005288585,0.0001339685,0.00005399681],"domain_scores_gemma":[0.9993976,0.0001823642,0.000120318,0.00003224382,0.0002213331,0.00004610151],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003729233,0.0001244481,0.7759563,0.0008165191,0.0001749038,0.002609766,0.02604061,0.001729569,0.004859942,0.003858632,0.003454309,0.1800021],"study_design_scores_gemma":[0.000006044064,0.0001038005,0.9094281,0.0001905873,0.0001103112,0.0007965947,0.06420998,0.001689388,0.002391053,0.001028042,0.02002039,0.00002575331],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.99009,0.0004891293,0.0005543592,0.0001347113,0.000008767892,0.00002730801,0.0004540788,0.00001432713,0.008227346],"genre_scores_gemma":[0.993393,0.0006844035,0.0009289162,0.00002028877,0.000003623447,0.00002952931,0.000477859,0.000007509332,0.004454955],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008579002,"threshold_uncertainty_score":0.01705813,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01852067729080104,"score_gpt":0.2014316732194854,"score_spread":0.1829109959286843,"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."}}