{"id":"W3088864553","doi":"10.30736/je.v5i2.513","title":"Pemanfaatan Quantum GIS Cloud Untuk Pemetaan Polygon Area Kandang Peternakan di Wilayah Kabupaten Probolinggo","year":2020,"lang":"en","type":"article","venue":"JE-UNISLA","topic":"Multimedia Learning Systems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"WiLAN (Canada)","funders":"","keywords":"Livestock; Animal husbandry; Agricultural science; Geography; Geographic information system; Business; Cartography; Forestry; Agriculture; Environmental science","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":[0.0003392711,0.00048897,0.0005544078,0.0008436237,0.0007968564,0.002064438,0.0008304133,0.000394864,0.03771206],"category_scores_gemma":[0.001104066,0.0003106443,0.0004722254,0.002026349,0.0003201063,0.002608398,0.001819787,0.0006190478,0.01461473],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007711106,"about_ca_system_score_gemma":0.00137238,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01454633,"about_ca_topic_score_gemma":0.01432219,"domain_scores_codex":[0.9996842,0.00002968392,0.00002270889,0.00008983853,0.0001163493,0.000057253],"domain_scores_gemma":[0.9996434,0.00005593571,0.00002302359,0.00008748528,0.0001432398,0.00004694241],"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":[0.001158921,0.0003640887,0.01073424,0.001162037,0.00008901631,0.001306212,0.001384102,0.02161689,0.01541796,0.03092305,0.3383412,0.5775023],"study_design_scores_gemma":[0.0001669867,0.00008411222,0.01452361,0.0002821907,0.00005643829,0.0006371631,0.002518226,0.1570905,0.01849778,0.02475831,0.7812403,0.0001444195],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1154329,0.002373179,0.4079397,0.0041469,0.001304546,0.001180281,0.1102665,0.08314703,0.2742091],"genre_scores_gemma":[0.5027258,0.003233079,0.3079986,0.0004539217,0.0001485371,0.001255496,0.1088637,0.003598794,0.07172205],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03771206,"threshold_uncertainty_score":0.1261594,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03521461943537012,"score_gpt":0.2428875684747994,"score_spread":0.2076729490394293,"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."}}