{"id":"W3173259049","doi":"10.30996/exp.v18i1.5210","title":"OPTIMASI PENGELOLAAN AIR BENDUNG CAWAK UNTUK DAERAH IRIGASI CAWAK DENGAN PROGRAM SOLVER (Studi kasus : Kemanteren Nglumber_Kecamatan Kepohbaru_Kabupaten Bojonegoro)","year":2021,"lang":"en","type":"article","venue":"EXTRAPOLASI","topic":"Multimedia Learning Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"WiLAN (Canada)","funders":"","keywords":"Irrigation; Sowing; Environmental science; Hydrology (agriculture); Drip irrigation; Cropping; Forestry; Geography; Agronomy; Engineering; Agriculture; Biology","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":[0.0004240311,0.0007733005,0.0004718492,0.0002560872,0.000344245,0.001180853,0.0005400605,0.0005865702,0.01488757],"category_scores_gemma":[0.001385826,0.0003327866,0.0004841328,0.0004272977,0.0003086516,0.0007519783,0.000424968,0.0009017147,0.001164791],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005159813,"about_ca_system_score_gemma":0.001742289,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009906469,"about_ca_topic_score_gemma":0.01524413,"domain_scores_codex":[0.999792,0.00005542445,0.000008946871,0.00005067385,0.00004846967,0.00004442125],"domain_scores_gemma":[0.9994668,0.0003305932,0.00004151413,0.00002944949,0.0001087599,0.00002289577],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002466647,0.0001752484,0.003223975,0.0004685187,0.00006919304,0.0001129788,0.0001291667,0.8834461,0.005385221,0.008397283,0.007056108,0.09128945],"study_design_scores_gemma":[0.00003499357,0.00007334958,0.0008229885,0.00004323318,0.00002461812,0.00003244894,0.0000979363,0.986701,0.002652367,0.002301216,0.007204882,0.00001095253],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3296208,0.001834544,0.5542558,0.001584103,0.0002734524,0.0003188259,0.002509179,0.004086422,0.1055168],"genre_scores_gemma":[0.7329791,0.0009665699,0.2347318,0.0002459997,0.00004048801,0.000389974,0.001489128,0.0009101467,0.02824684],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01488757,"threshold_uncertainty_score":0.04980391,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01557428871807686,"score_gpt":0.2686458788881637,"score_spread":0.2530715901700868,"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."}}