{"id":"W2011329242","doi":"10.1002/ird.311","title":"An irrigation management model for a multi‐cropping and multi‐pattern setting","year":2007,"lang":"en","type":"article","venue":"Irrigation and Drainage","topic":"Irrigation Practices and Water Management","field":"Agricultural and Biological Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Cropping; Irrigation; Agricultural engineering; Evapotranspiration; Irrigation management; Water resource management; Environmental science; Plot (graphics); Current (fluid); Water resources; Computer science; Engineering; Mathematics; Agriculture; Geography; Ecology","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":[0.00087102,0.0001405782,0.0001033091,0.00003356163,0.0004414589,0.0002152679,0.00008779739,0.00006346586,0.00001535709],"category_scores_gemma":[0.00001476933,0.00007250311,0.00003243861,0.0001031181,0.00004152214,0.0005221969,0.00005647281,0.00006218602,0.000003859529],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002223845,"about_ca_system_score_gemma":0.00000168603,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009194577,"about_ca_topic_score_gemma":0.0003373969,"domain_scores_codex":[0.998956,0.00003551399,0.0002559124,0.0003590139,0.0001380585,0.0002554877],"domain_scores_gemma":[0.9995587,0.00006344653,0.0001435877,0.0000585081,0.00005989457,0.0001158038],"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":[0.00005381732,0.0001685899,0.0009809952,0.0001310692,0.00003341904,0.000007417823,0.002257388,0.0002656541,0.02821381,0.05912203,0.00003726215,0.9087285],"study_design_scores_gemma":[0.0008736194,0.0001054089,0.1006103,0.00003827362,0.00004283815,0.000003588822,0.002321904,0.8743257,0.0006082673,0.01921939,0.001564329,0.0002863424],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6142489,0.00005946539,0.3765914,0.00200396,0.0001182262,0.001183269,0.00003270329,0.000166148,0.005595829],"genre_scores_gemma":[0.9759711,0.000003234568,0.02208847,0.001000343,0.00007408925,0.00003400268,0.0001372103,0.00000253783,0.000689009],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9084422,"threshold_uncertainty_score":0.3395389,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04935267659005377,"score_gpt":0.2982877908753446,"score_spread":0.2489351142852909,"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."}}