{"id":"W4410068707","doi":"10.3390/w17091384","title":"An Overview of Evapotranspiration Estimation Models Utilizing Artificial Intelligence","year":2025,"lang":"en","type":"article","venue":"Water","topic":"Plant Water Relations and Carbon Dynamics","field":"Environmental Science","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Evapotranspiration; Estimation; Environmental science; Computer science; Artificial intelligence; Remote sensing; Geography; Engineering; Ecology; Systems engineering; Biology","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":[0.0008359354,0.001252137,0.0008195029,0.001561707,0.0002687743,0.001433692,0.001550437,0.001085586,0.001750077],"category_scores_gemma":[0.001159651,0.0005484507,0.001288154,0.002620756,0.0003077419,0.001518152,0.0006159891,0.001149139,0.0010478],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005722582,"about_ca_system_score_gemma":0.0007622986,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00331923,"about_ca_topic_score_gemma":0.001981928,"domain_scores_codex":[0.9996706,0.00007060341,0.00005406484,0.00008140147,0.0001028326,0.00002044155],"domain_scores_gemma":[0.9995559,0.0002368274,0.00004684216,0.00002829944,0.0001181286,0.00001409088],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007719962,0.0001510086,0.004347516,0.004331958,0.0003353296,0.0002887748,0.0001388498,0.2098433,0.004554018,0.04204128,0.009151277,0.7247395],"study_design_scores_gemma":[0.00001586312,0.0002158361,0.003865504,0.001424942,0.0003228166,0.000444901,0.00007961701,0.7373983,0.004013759,0.04360439,0.2084733,0.0001407364],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.009165013,0.2854546,0.6812289,0.001486566,0.0006124844,0.000176369,0.0006140255,0.0009367357,0.02032535],"genre_scores_gemma":[0.1420041,0.5278721,0.3149875,0.0006310085,0.001714041,0.0004330497,0.00185064,0.0002434644,0.01026413],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.00331923,"threshold_uncertainty_score":0.006599844,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06219388677361695,"score_gpt":0.2981716875217041,"score_spread":0.2359778007480871,"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."}}