{"id":"W3124117084","doi":"","title":"Farm-based measures for reducing human and environmental health risks from chemical constituents in wastewater","year":2010,"lang":"en","type":"article","venue":"CGSPace A Repository of Agricultural Research Outputs (Consultative Group for International Agricultural Research)","topic":"Wastewater Treatment and Reuse","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Sri lanka; Wastewater; International waters; Irrigation; Human health; International development; Research centre; Water resource management; Environmental science; Environmental planning; Business; Environmental engineering; Environmental health; Political science; Economic growth; Economics; Library science; Medicine; Ecology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00159895,0.000522556,0.0005297546,0.001119011,0.0006142787,0.001314314,0.001406722,0.001776768,0.005232606],"category_scores_gemma":[0.001614652,0.0002040037,0.0006731651,0.001073192,0.0007452452,0.0009373467,0.001242164,0.0006804866,0.0007249653],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001157621,"about_ca_system_score_gemma":0.003760993,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009794784,"about_ca_topic_score_gemma":0.0216321,"domain_scores_codex":[0.9991981,0.0002800375,0.00004519667,0.00008524753,0.0003278313,0.0000636569],"domain_scores_gemma":[0.9994468,0.000125245,0.0001609344,0.00005336861,0.0001577285,0.00005591261],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0005224622,0.004750014,0.01229045,0.00385977,0.0003110947,0.0001817594,0.0006326479,0.005476973,0.04991062,0.006932195,0.03220206,0.88293],"study_design_scores_gemma":[0.001470072,0.0179355,0.3022642,0.003382919,0.001284839,0.001430507,0.007154473,0.008724415,0.1331802,0.04954771,0.4733362,0.0002889311],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4747143,0.173483,0.1258739,0.1021622,0.002786105,0.003830737,0.003546101,0.002361324,0.1112422],"genre_scores_gemma":[0.8334359,0.06201277,0.07742692,0.008542513,0.000372536,0.001042135,0.0008456475,0.00006756723,0.01625387],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009794784,"threshold_uncertainty_score":0.01947552,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06128494540303565,"score_gpt":0.3418720239283434,"score_spread":0.2805870785253077,"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."}}