{"id":"W2800974643","doi":"10.25077/jtpa.22.1.1-12.2018","title":"APLIKASI HISTOGRAM UNTUK ANALISIS VARIABILITAS TEMPORAL DAN SPASIAL HUJAN BULANAN: STUDI DI WILAYAH UPT PSDA DI PASURUAN JAWA TIMUR","year":2018,"lang":"id","type":"article","venue":"Jurnal Teknologi Pertanian Andalas","topic":"Computer Science and Engineering","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"WiLAN (Canada)","funders":"","keywords":"Forestry; 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":[0.006755991,0.0005428357,0.0007476149,0.002272596,0.0009027984,0.003231836,0.0008867004,0.0007903143,0.01980693],"category_scores_gemma":[0.02815406,0.0004307806,0.001238914,0.003735257,0.001024315,0.002478838,0.001397704,0.001602471,0.002983178],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00143941,"about_ca_system_score_gemma":0.001764483,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01783848,"about_ca_topic_score_gemma":0.01457407,"domain_scores_codex":[0.9958357,0.001173621,0.0003721696,0.0008288426,0.001420358,0.0003692418],"domain_scores_gemma":[0.9661525,0.01996407,0.003117334,0.001683797,0.008057903,0.001024356],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002473584,0.0005442358,0.5874138,0.0020695,0.0008096285,0.0004618111,0.02516193,0.002404585,0.003645363,0.004933176,0.0294541,0.3406282],"study_design_scores_gemma":[0.00003569578,0.0008216514,0.9188403,0.0005549499,0.0004877311,0.000390654,0.03013513,0.002924247,0.002788245,0.002726381,0.04015441,0.0001406207],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9321758,0.004997768,0.01300201,0.002162322,0.0004863091,0.0003595988,0.006321866,0.0009865705,0.0395078],"genre_scores_gemma":[0.976397,0.00112903,0.005624182,0.0002724649,0.00008089227,0.0003227416,0.002332276,0.0001907596,0.01365072],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01980693,"threshold_uncertainty_score":0.06626076,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01840613804318377,"score_gpt":0.2465918619183647,"score_spread":0.2281857238751809,"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."}}