{"id":"W4396229086","doi":"10.61860/jigp.v2i3.61","title":"ANALISIS KRITIS OPTIMALISASI POTENSI DIGITALISASI LAYANAN SESUAI KARAKTERISTIK MASYARAKAT DAN DEMOGRAFI WILAYAH PROVINSI SUMATERA UTARA","year":2024,"lang":"id","type":"article","venue":"JURNAL ILMIAH GEMA PERENCANA","topic":"SMEs Development and Digital Marketing","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Encana (Canada)","funders":"","keywords":"Geology","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":[0.001516231,0.001347164,0.00135959,0.0008401335,0.001606633,0.008799821,0.001434807,0.0007075631,0.0008123981],"category_scores_gemma":[0.0006886997,0.001315915,0.00093442,0.00261377,0.00110021,0.003557533,0.0006381508,0.001121535,0.000525102],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001109167,"about_ca_system_score_gemma":0.002054201,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004670341,"about_ca_topic_score_gemma":0.002383317,"domain_scores_codex":[0.9908994,0.0005573737,0.001823701,0.001982969,0.002236929,0.002499567],"domain_scores_gemma":[0.9962304,0.0005544617,0.0004922774,0.0007550489,0.0006131626,0.0013547],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0008461344,0.001170335,0.5199225,0.003717547,0.003561565,0.01684731,0.05437576,0.0001902032,0.0009196645,0.01354128,0.1936738,0.1912339],"study_design_scores_gemma":[0.001969091,0.001011955,0.2179406,0.006887315,0.001248228,0.001297586,0.04614905,0.003821497,0.0005284614,0.0009147399,0.7117873,0.006444183],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8261378,0.005121389,0.0000387546,0.002855369,0.004139146,0.0008278986,0.0004240131,0.0005676809,0.1598879],"genre_scores_gemma":[0.983463,0.001383303,0.0003224697,0.0009273367,0.002045584,0.00006848775,0.0003589493,0.0002158963,0.01121494],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5181136,"threshold_uncertainty_score":0.9999279,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02127456361197223,"score_gpt":0.2760998519105939,"score_spread":0.2548252882986217,"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."}}