{"id":"W3092459197","doi":"10.1002/aic.17096","title":"Consensus‐based approach for parameter and state estimation of agro‐hydrological systems","year":2020,"lang":"en","type":"article","venue":"AIChE Journal","topic":"Irrigation Practices and Water Management","field":"Agricultural and Biological Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Discretization; Kalman filter; Nonlinear system; Estimation theory; Richards equation; Computer science; Mathematical optimization; Work (physics); Estimation; Mathematics; Algorithm; Soil water; Artificial intelligence; Engineering; Soil science; Environmental science","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":[0.0009257081,0.0006019162,0.001122095,0.0006170365,0.0004375142,0.0006537616,0.001181106,0.001044688,0.001475099],"category_scores_gemma":[0.002601756,0.0004365179,0.000540201,0.0005729678,0.0006458951,0.0009488654,0.0009301587,0.0009918521,0.000254241],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006888187,"about_ca_system_score_gemma":0.001202797,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007869619,"about_ca_topic_score_gemma":0.003946363,"domain_scores_codex":[0.9994282,0.0001424717,0.00003426451,0.0001773915,0.0001573444,0.00006014939],"domain_scores_gemma":[0.9987072,0.0006145735,0.0001840477,0.0001051344,0.0003452214,0.00004383923],"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":[0.00004194544,0.00001962238,0.0002495256,0.00004554763,0.00003554222,0.00004457572,0.00004756088,0.9644182,0.002001372,0.004051399,0.0002758195,0.02876888],"study_design_scores_gemma":[0.00000422804,0.000009901175,0.00004379469,0.000001605156,0.00000271953,0.000003434194,0.00000363546,0.9985378,0.0002865818,0.0009916588,0.0001112611,0.000003372472],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008908133,0.00009523817,0.9899192,0.00005910468,0.00001962001,0.00001521753,0.00001508041,0.0001840927,0.0007842731],"genre_scores_gemma":[0.8988491,0.0001765024,0.09870449,0.00007787573,0.00004563366,0.0001189753,0.00009150583,0.00003938218,0.001896417],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007869619,"threshold_uncertainty_score":0.01564765,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05686453198917116,"score_gpt":0.2452758878711956,"score_spread":0.1884113558820245,"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."}}