{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001040274,0.0009313755,0.001109313,0.0003733134,0.000751679,0.0009478102,0.002739493,0.0004433501,0.0001855217],"category_scores_gemma":[0.000294326,0.0009484461,0.0004732044,0.00155274,0.0002445698,0.001395034,0.00120708,0.001323533,0.0006009539],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003800526,"about_ca_system_score_gemma":0.0007374495,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005499878,"about_ca_topic_score_gemma":0.0008762009,"domain_scores_codex":[0.9924216,0.0008114608,0.001289202,0.002153164,0.001466755,0.001857808],"domain_scores_gemma":[0.9949442,0.0003915011,0.0005279474,0.002767227,0.000582205,0.0007869618],"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":[0.0001948129,0.006484234,0.2498278,0.001754256,0.003271251,0.01458499,0.0616005,0.002404834,0.06410131,0.02555299,0.05965851,0.5105645],"study_design_scores_gemma":[0.0128427,0.001869989,0.3411469,0.001958234,0.0005223581,0.005450709,0.004121208,0.1904236,0.04654201,0.001138952,0.3854846,0.008498804],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8343972,0.01134211,0.05673856,0.006281064,0.01517628,0.006217239,0.0001199972,0.009429769,0.0602978],"genre_scores_gemma":[0.9355017,0.0000768648,0.0584492,0.0002699229,0.0007618175,0.0002984335,0.0001069218,0.0001569652,0.004378197],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5020657,"threshold_uncertainty_score":0.9992966,"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."}}