{"id":"W2593833973","doi":"10.5539/jsd.v10n2p1","title":"Obstacles to Low Quality Water Irrigation of Food Crops in Morogoro, Tanzania","year":2017,"lang":"en","type":"article","venue":"Journal of Sustainable Development","topic":"Wastewater Treatment and Reuse","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Udenrigsministeriet","keywords":"Tanzania; Irrigation; Effluent; Agriculture; Livelihood; Business; Wastewater; Water quality; Environmental science; Urban agriculture; Irrigation management; Water resource management; Environmental planning; Geography; Environmental engineering; Agronomy; Ecology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008275139,0.000123412,0.0002414573,0.0001023747,0.000197206,0.00007163677,0.0003953869,0.00004978999,0.0001931634],"category_scores_gemma":[0.00006739049,0.0000791931,0.00005085743,0.00006491,0.0000701213,0.0005158537,0.0003004662,0.00008716568,0.00003597598],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006295609,"about_ca_system_score_gemma":0.00006549021,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000256516,"about_ca_topic_score_gemma":0.0002109288,"domain_scores_codex":[0.9984845,0.00004315178,0.00059121,0.0001352375,0.0004078864,0.0003379947],"domain_scores_gemma":[0.9992266,0.00001332956,0.0003358504,0.0002353576,0.00007065982,0.0001182166],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005385616,0.00119698,0.8318985,0.0002728747,0.0001821498,0.0008852492,0.03799029,0.003222981,0.1149552,0.0006664357,0.001068544,0.007122266],"study_design_scores_gemma":[0.0007964963,0.0001602346,0.6734653,0.00005242302,0.000007118155,0.000007721568,0.002715174,0.000002432148,0.3193227,0.00111665,0.002226351,0.000127402],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9980087,0.0000190178,0.00004637236,0.0005989759,0.00008407624,0.0002018986,5.993037e-7,0.000003062489,0.001037266],"genre_scores_gemma":[0.9944867,0.000005332937,0.002982459,0.00003055159,0.00001844609,0.00000624243,0.000001235305,0.000008788958,0.002460226],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2043675,"threshold_uncertainty_score":0.3229401,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01517666102384828,"score_gpt":0.2496778628350211,"score_spread":0.2345012018111728,"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."}}