{"id":"W2972849357","doi":"10.1002/aic.16795","title":"Optimal sensor placement for agro‐hydrological systems","year":2019,"lang":"en","type":"article","venue":"AIChE Journal","topic":"Irrigation Practices and Water Management","field":"Agricultural and Biological Sciences","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Observability; Discretization; Computer science; Linearization; Mathematical optimization; Nonlinear system; Reduction (mathematics); Scale (ratio); State space; Control theory (sociology); Mathematics; Applied mathematics; Control (management); Artificial intelligence; Statistics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0005181197,0.0005596835,0.0007137008,0.0003777006,0.0003173048,0.0004592518,0.0005840834,0.0007907272,0.001111838],"category_scores_gemma":[0.001976852,0.0003820738,0.0003942662,0.0003512354,0.000665325,0.0006895524,0.0007658986,0.0005212469,0.0001530889],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005129948,"about_ca_system_score_gemma":0.000766909,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002523601,"about_ca_topic_score_gemma":0.002276839,"domain_scores_codex":[0.9995752,0.0001758099,0.00001834856,0.00009792623,0.00008360599,0.00004902617],"domain_scores_gemma":[0.999196,0.0004972339,0.0001134074,0.00006809668,0.00009688491,0.00002849188],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000670979,0.00003097243,0.0004308399,0.00005853192,0.00001348848,0.00006447163,0.00004141492,0.971169,0.006417088,0.003899861,0.0002041584,0.01760313],"study_design_scores_gemma":[0.000008093696,0.00002588704,0.0001342403,0.000003411692,0.000002817916,0.000009781668,0.00001409451,0.9956354,0.001334919,0.002655844,0.0001711934,0.000004318681],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03929403,0.0001610547,0.9589689,0.00008364449,0.00001922017,0.00003776591,0.00003109387,0.0001587115,0.001245598],"genre_scores_gemma":[0.8505049,0.0001402347,0.1485211,0.00002411234,0.0000109218,0.00006384905,0.00004953726,0.00001688197,0.0006684805],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002523601,"threshold_uncertainty_score":0.005017817,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02485574436287584,"score_gpt":0.2374838361468561,"score_spread":0.2126280917839803,"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."}}