{"id":"W7117750055","doi":"10.3390/agriculture16010093","title":"Optimization of Sensor Combinations for Simplified Estimation of Reference Crop Evapotranspiration Using Machine Learning and SHAP Interpretation","year":2025,"lang":"en","type":"article","venue":"Agriculture","topic":"Plant Water Relations and Carbon Dynamics","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministry of Agriculture","funders":"","keywords":"Interpretability; Evapotranspiration; Random forest; Estimation; Linear regression; Regression; Interpretation (philosophy); Regression analysis","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007150778,0.00005899797,0.00008419865,0.00003475412,0.00007584004,0.00001120305,0.00003383712,0.00006217252,0.00001154869],"category_scores_gemma":[0.00003691345,0.00004624317,0.00001905251,0.0001783108,0.00003103487,0.0001401562,0.0000156439,0.0000499823,2.669244e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003142704,"about_ca_system_score_gemma":0.000004718112,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009353784,"about_ca_topic_score_gemma":0.00003863054,"domain_scores_codex":[0.9995705,0.00002507454,0.000177668,0.0001033889,0.00007293367,0.00005035994],"domain_scores_gemma":[0.9997578,0.00003635627,0.0001174081,0.00003757411,0.00003941904,0.00001139153],"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":[0.00001229823,0.00002498677,0.003994792,0.00003303484,0.000007482648,2.43844e-8,0.00017944,0.9612301,0.03229699,0.001047386,0.000003460794,0.001169992],"study_design_scores_gemma":[0.0002411039,0.00003350117,0.003986908,0.00004353867,0.00004522162,0.000001035816,0.00002287971,0.9927564,0.002375734,0.000406837,0.00003767381,0.00004921768],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5705227,0.0000278215,0.428506,0.00006821939,0.00001999875,0.0002366258,0.00003489141,0.00001220708,0.0005714977],"genre_scores_gemma":[0.9804543,0.00001721116,0.01905509,0.000009251891,0.000001534695,0.000007111285,0.000310122,0.000002378303,0.000142947],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4099316,"threshold_uncertainty_score":0.1885742,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00850847280335089,"score_gpt":0.235875885492702,"score_spread":0.2273674126893511,"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."}}