{"id":"W4239582258","doi":"10.31219/osf.io/5bzgf","title":"APLIKASI SISTEM INFORMASI GEOGRAFIS (SIG) UNTUK IDENTIFIKASI PERUBAHAN SEMPADAN SUNGAI MUSI DI KOTA PALEMBANG (1922 - 2012)","year":2017,"lang":"id","type":"preprint","venue":"","topic":"Multimedia Learning Systems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"WiLAN (Canada)","funders":"","keywords":"Forestry; Geoprocessing; Humanities; Geography; Physics; Cartography; Art","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","open_science","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow","open_science","research_integrity","insufficient_payload"],"category_scores_codex":[0.006531969,0.003217924,0.003772449,0.001402066,0.003190199,0.01177248,0.01619831,0.002607207,0.0009867962],"category_scores_gemma":[0.001338163,0.003160639,0.002140986,0.0008563927,0.001125686,0.004543636,0.01445976,0.005117137,0.007451801],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001063598,"about_ca_system_score_gemma":0.001938645,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003869638,"about_ca_topic_score_gemma":0.003259557,"domain_scores_codex":[0.9802928,0.0017264,0.004308206,0.005177895,0.004525295,0.003969427],"domain_scores_gemma":[0.9767238,0.001139987,0.005201395,0.01312902,0.001698177,0.002107655],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003813964,0.003235138,0.2405128,0.0227654,0.007601113,0.002916729,0.121202,0.01054149,0.002773743,0.02796557,0.1924212,0.3676834],"study_design_scores_gemma":[0.002356479,0.0003587584,0.07684181,0.003878192,0.0004245699,0.0003985283,0.001479977,0.148116,0.0007199948,0.0001622845,0.7601307,0.005132709],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.115734,0.009495839,0.272227,0.01152667,0.1544366,0.01970913,0.0002476565,0.008562315,0.4080608],"genre_scores_gemma":[0.5163257,0.0008254516,0.01067966,0.0006867165,0.005225743,0.0008219376,0.0006484817,0.0004726343,0.4643137],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.5677095,"threshold_uncertainty_score":0.9999264,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03153553542266261,"score_gpt":0.2783627679417629,"score_spread":0.2468272325191003,"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."}}