{"id":"W4240771425","doi":"10.12777/mkts.20.2.155-166","title":"Kajian Optimalisasi Sistem Irigasi Rawa (Studi Kasus Daerah Rawa Semangga Kabupaten Merauke Propinsi Papua)","year":2015,"lang":"id","type":"article","venue":"MEDIA KOMUNIKASI TEKNIK SIPIL","topic":"Plant Growth and Agriculture Techniques","field":"Agricultural and Biological Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"WiLAN (Canada)","funders":"","keywords":"Swamp; Irrigation; Dry season; Water balance; Agriculture; Cropping; Geography; Wet season; Environmental science; Water resources; Agroforestry; Water resource management; Hydrology (agriculture); Biology; Ecology; Cartography; Engineering","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","insufficient_payload"],"consensus_categories":["metaepi_narrow"],"category_scores_codex":[0.001741922,0.001625966,0.001858723,0.0001441556,0.001170307,0.0009323946,0.002429742,0.001242821,0.0003089564],"category_scores_gemma":[0.0009095935,0.0007325411,0.0007195841,0.001789009,0.0009434044,0.0008459265,0.000903158,0.001445329,0.0009063111],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004232077,"about_ca_system_score_gemma":0.0003249118,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001840838,"about_ca_topic_score_gemma":0.002528634,"domain_scores_codex":[0.9911714,0.001027523,0.001585399,0.001874703,0.002013998,0.002327035],"domain_scores_gemma":[0.994785,0.0007230718,0.0008741419,0.0006846754,0.000899796,0.002033354],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001421604,0.003384161,0.0294183,0.0007782872,0.001099068,0.0025033,0.01269053,0.00003109413,0.2601436,0.004527838,0.5611799,0.1228223],"study_design_scores_gemma":[0.001940583,0.001916726,0.0397488,0.0007087621,0.0003748533,0.0003641653,0.004904483,0.00009831628,0.02980638,0.0004155389,0.9171156,0.002605778],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9227371,0.01117454,0.00001385958,0.01883814,0.003964589,0.003305185,0.0007598589,0.002290696,0.03691601],"genre_scores_gemma":[0.9595711,0.002468184,0.002026082,0.002048228,0.006258684,0.0004249328,0.00254147,0.0000540084,0.0246073],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3559357,"threshold_uncertainty_score":0.9998716,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05581263429910824,"score_gpt":0.2307538182941277,"score_spread":0.1749411839950195,"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."}}