{"id":"W2956048521","doi":"10.29122/jai.v7i1.2406","title":"PENGEMBANGAN DATABASE PENGELOLAAN SUMBER DAYA AIR UNTUK WILAYAH KABUPATEN PANDEGLANG","year":2018,"lang":"en","type":"article","venue":"Jurnal Air Indonesia","topic":"Water Quality Monitoring Technologies","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Encana (Canada); WiLAN (Canada)","funders":"","keywords":"Water resources; Water resource management; Irrigation; Government (linguistics); Sustainable management; Resource (disambiguation); Unit (ring theory); Swamp; Environmental science; Environmental resource management; Business; Sustainability; Computer science; Mathematics","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":[],"category_scores_codex":[0.0005517133,0.0003311769,0.0002997407,0.0001075386,0.0003922181,0.00005821244,0.001008619,0.0001972978,0.0004585813],"category_scores_gemma":[0.00006694713,0.0002823817,0.000095704,0.0004514824,0.000672537,0.0006653077,0.0009719236,0.0004713938,0.002084643],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002247778,"about_ca_system_score_gemma":0.00002312688,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009314892,"about_ca_topic_score_gemma":0.0002128373,"domain_scores_codex":[0.9974914,0.0001377167,0.0003992935,0.0006156701,0.0006662422,0.0006897414],"domain_scores_gemma":[0.9986072,0.00006789411,0.0001724591,0.0009264393,0.00002946505,0.0001965375],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006680217,0.0001443329,0.9594284,0.00001918656,0.00003198778,0.0001119371,0.0005602638,0.0000292099,0.02411282,0.0001300799,0.009804656,0.005560379],"study_design_scores_gemma":[0.0005100323,0.0002021056,0.926752,0.00004805476,0.00003077033,0.00007928033,0.0002855288,0.00008039745,0.05806864,0.0002115399,0.01328152,0.0004501621],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9928219,0.00002974786,0.0001305177,0.001404696,0.0005545863,0.0002381707,0.00002631613,0.0005543231,0.004239685],"genre_scores_gemma":[0.9978834,0.00001569307,0.0009176923,0.0002238563,0.0005323594,0.00003079857,0.00002499362,0.00004838848,0.0003228484],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03395582,"threshold_uncertainty_score":0.9999628,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02784031117496557,"score_gpt":0.2670767990419461,"score_spread":0.2392364878669806,"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."}}