{"id":"W3120422917","doi":"10.31849/teknik.v14i2.5041","title":"Aplikasi Sistem Informasi Geografis (SIG) untuk Prediksi Erosi Lahan dengan Metode MUSLE","year":2020,"lang":"id","type":"article","venue":"JURNAL TEKNIK","topic":"Edcuational Technology Systems","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Encana (Canada)","funders":"","keywords":"Forestry; Physics; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001061728,0.0006079583,0.0004530294,0.001134232,0.0004710068,0.002916822,0.0003810146,0.0005692607,0.01377503],"category_scores_gemma":[0.003507378,0.0002898396,0.000537861,0.002057928,0.0004029668,0.001567969,0.0008012792,0.0005348991,0.00288454],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00101872,"about_ca_system_score_gemma":0.001260994,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02161423,"about_ca_topic_score_gemma":0.02278194,"domain_scores_codex":[0.9994417,0.0001243272,0.00003903469,0.000129134,0.0002022506,0.00006348155],"domain_scores_gemma":[0.9981745,0.0008167729,0.000160389,0.0001659163,0.0006295644,0.0000527829],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004810049,0.000166498,0.5757011,0.001107899,0.0005409998,0.0008776959,0.003290243,0.0363421,0.01798912,0.01120447,0.01742767,0.3348713],"study_design_scores_gemma":[0.00004302775,0.0002843661,0.7651379,0.0002524183,0.0005003192,0.001027845,0.007365524,0.0778082,0.0150352,0.01314859,0.119199,0.0001976675],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8405026,0.002816037,0.06889757,0.001952963,0.0001746819,0.0001944971,0.01237905,0.003705693,0.06937696],"genre_scores_gemma":[0.9676567,0.0008321622,0.01259396,0.0001047381,0.00004143424,0.00007174024,0.004405674,0.0001608853,0.01413264],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02161423,"threshold_uncertainty_score":0.04608202,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0321706814662169,"score_gpt":0.2424928226161201,"score_spread":0.2103221411499032,"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."}}