{"id":"W3199335793","doi":"10.1061/(asce)ir.1943-4774.0001638","title":"Discussion of “Model Development for Estimation of Sediment Removal Efficiency of Settling Basins Using Group Methods of Data Handling” by Faisal Ahmad, Mujib Ahmad Ansari, Ajmal Hussain, and Jahangeer Jahangeer","year":2021,"lang":"en","type":"article","venue":"Journal of Irrigation and Drainage Engineering","topic":"Hydrological Forecasting Using AI","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"","keywords":"Settling; Sediment; Estimation; Environmental science; Geology; Mathematics; Environmental engineering; Geomorphology; Economics; Management","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004138987,0.0005891572,0.0005749442,0.0004717786,0.0006988791,0.001279144,0.001980113,0.001904389,0.003029936],"category_scores_gemma":[0.007637706,0.0003157583,0.001892257,0.0006637059,0.000660965,0.001671192,0.0008294893,0.002017493,0.0008895916],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006615678,"about_ca_system_score_gemma":0.001498778,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01246289,"about_ca_topic_score_gemma":0.00741173,"domain_scores_codex":[0.999052,0.0004887326,0.00006431733,0.00010391,0.0002434172,0.00004759166],"domain_scores_gemma":[0.9978335,0.001174808,0.00007031074,0.0001953566,0.0006764675,0.00004957321],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001182379,0.0001278066,0.004095289,0.0003254623,0.0002403604,0.000486666,0.0003289551,0.7409793,0.00395923,0.1200871,0.04234998,0.08690156],"study_design_scores_gemma":[0.000021052,0.00007635577,0.0007846102,0.00004270579,0.00004143548,0.00008093701,0.00006486011,0.9307137,0.004370767,0.03985783,0.02390647,0.00003926064],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"commentary","genre_scores_codex":[0.007140591,0.0004694571,0.9790475,0.00814129,0.001374857,0.00007935194,0.000228518,0.0006431774,0.002875255],"genre_scores_gemma":[0.3410146,0.001502308,0.6228806,0.006764648,0.002857726,0.0007691147,0.001125976,0.0005142524,0.02257084],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.01246289,"threshold_uncertainty_score":0.02478069,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04769757137190654,"score_gpt":0.3217105402790771,"score_spread":0.2740129689071705,"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."}}