{"id":"W4388852479","doi":"10.2166/wpt.2023.209","title":"Characterizing hydrological-sensitive areas of the Kinyerezi river sub-catchments in Dar es Salaam, Tanzania using the topographic index approach","year":2023,"lang":"en","type":"article","venue":"Water Practice & Technology","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Water Institute of the Gulf","keywords":"Surface runoff; Hydrology (agriculture); Drainage basin; Tributary; Environmental science; Infiltration (HVAC); Silt; Geology; Geography; Geomorphology; Cartography","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008842335,0.0002103294,0.0002660708,0.0002079709,0.0003541945,0.00001506552,0.0005872896,0.0002367937,0.00002664792],"category_scores_gemma":[0.0001409727,0.0001107802,0.0000685877,0.001046404,0.001630877,0.0003152589,0.001743021,0.0005160502,0.0001160942],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007241619,"about_ca_system_score_gemma":0.000004432647,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003304352,"about_ca_topic_score_gemma":0.00004301892,"domain_scores_codex":[0.9981115,0.0003038383,0.0003122797,0.0004650893,0.0002482563,0.0005589958],"domain_scores_gemma":[0.9991285,0.00011408,0.0002019628,0.0005198347,0.00001423025,0.00002143865],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001364745,0.0002872712,0.9360657,0.00001758395,0.0001840223,0.00009746796,0.004275796,0.002908127,0.05436341,0.000571956,0.0001314514,0.0009607171],"study_design_scores_gemma":[0.001247365,0.0002110787,0.8597456,0.00004688895,0.0002875121,0.0001492004,0.005811773,0.006735843,0.1024564,0.01033994,0.01234326,0.0006250797],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9851067,0.00001269635,0.0001700793,0.01250597,0.0001287725,0.0004866867,0.000002404179,0.0001169649,0.001469745],"genre_scores_gemma":[0.9986672,0.00008744353,0.0001493886,0.0009397143,0.00001318609,0.00005731451,0.000004033233,0.00001460669,0.00006704842],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07632007,"threshold_uncertainty_score":0.6009035,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01543413906561734,"score_gpt":0.23772281445514,"score_spread":0.2222886753895227,"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."}}