{"id":"W4413406579","doi":"10.56799/ekoma.v4i5.10579","title":"Pengelolaan Manajemen Kemiskinan Ekstrem Terhadap Penurunan Angka Stunting Di Kabupaten Musi Banyuasin","year":2025,"lang":"id","type":"article","venue":"EKOMA Jurnal Ekonomi Manajemen Akuntansi","topic":"Economic Growth and Fiscal Policies","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Encana (Canada)","funders":"","keywords":"Geography","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":["metaepi_narrow","sts","scholarly_communication"],"consensus_categories":["metaepi_narrow"],"category_scores_codex":[0.00165325,0.001596154,0.002597073,0.001730088,0.001338846,0.001514722,0.002270622,0.0008726406,0.000411185],"category_scores_gemma":[0.0002402583,0.002044316,0.001114007,0.001146664,0.0005515017,0.001432327,0.001174194,0.001606167,0.0007065528],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001758773,"about_ca_system_score_gemma":0.0003691064,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001007351,"about_ca_topic_score_gemma":0.001283956,"domain_scores_codex":[0.9904696,0.0001880509,0.003951249,0.002453494,0.0002171365,0.002720475],"domain_scores_gemma":[0.9948238,0.000299661,0.00208201,0.001830021,0.0001661739,0.0007983126],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003391381,0.0006301932,0.8190159,0.000789104,0.00156118,0.0001621855,0.001543345,0.0001078358,0.0001024228,0.1556714,0.009325361,0.01075187],"study_design_scores_gemma":[0.003689328,0.0004245307,0.7087535,0.0006335994,0.0003035362,0.00003419662,0.00215123,0.003158993,0.0003232338,0.002974027,0.2755288,0.002025019],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6203793,0.008541403,0.0004012898,0.006376592,0.003829051,0.001250369,0.0001642105,0.0001935732,0.3588642],"genre_scores_gemma":[0.9591432,0.001919578,0.0001769963,0.002399678,0.001170424,0.0001288738,0.0001413635,0.0002415698,0.03467837],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3387638,"threshold_uncertainty_score":0.9999613,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01833359716917235,"score_gpt":0.2205665979894106,"score_spread":0.2022330008202382,"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."}}