{"id":"W4320158993","doi":"10.35475/riptek.v15i2.122","title":"PENGGUNAAN SISTEM INFORMASI GEOGRAFIS DALAM PENENTUAN KESESUAIAN LOKASI SARANA PENDIDIKAN MENENGAH DI KECAMATAN MIJEN","year":2021,"lang":"en","type":"article","venue":"Jurnal Riptek","topic":"Decision Support System Applications","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Encana (Canada)","funders":"","keywords":"Mindset; Geographic information system; Service (business); Vocational education; Function (biology); Population; Business; Analytic hierarchy process; Transport engineering; Computer science; Marketing; Geography; Operations research; Engineering; Economic growth; Cartography; Sociology","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":[0.0008087966,0.0002934512,0.0003486807,0.001818889,0.0009847423,0.002919748,0.0004011283,0.0004409539,0.03219752],"category_scores_gemma":[0.001684497,0.0002094094,0.0001755238,0.00307933,0.0004042785,0.001006181,0.001004545,0.0005640776,0.005849234],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001252123,"about_ca_system_score_gemma":0.003429804,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01580033,"about_ca_topic_score_gemma":0.01935438,"domain_scores_codex":[0.9995524,0.00006933667,0.0000476126,0.00007096571,0.0001963311,0.00006325168],"domain_scores_gemma":[0.9989412,0.0002726723,0.00008762416,0.00006787822,0.0005583731,0.00007221747],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00054793,0.0003519824,0.08600761,0.003748361,0.0001043811,0.004031209,0.01133578,0.003987977,0.009000657,0.03504615,0.2748837,0.5709543],"study_design_scores_gemma":[0.0000218482,0.000061818,0.08449304,0.000460657,0.00004428838,0.0007020879,0.007451095,0.001511139,0.003230869,0.001965706,0.9000003,0.00005725311],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.4053681,0.01338755,0.01297557,0.01066764,0.001868032,0.001532502,0.03502692,0.00184296,0.5173308],"genre_scores_gemma":[0.6835076,0.01285793,0.0291095,0.0008458599,0.0002652906,0.000965088,0.03293765,0.0002576268,0.2392534],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03219752,"threshold_uncertainty_score":0.1077114,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02187177447603593,"score_gpt":0.2417974501464252,"score_spread":0.2199256756703893,"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."}}