{"id":"W2790259156","doi":"10.2134/cs2018.51.0206","title":"Subsurface drip irrigation in Ontario","year":2018,"lang":"en","type":"article","venue":"Crops & Soils","topic":"Irrigation Practices and Water Management","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Drip irrigation; Environmental science; Hydrology (agriculture); Water resource management; Irrigation; Agricultural engineering; Engineering; Agronomy; Geotechnical engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0001748615,0.000122242,0.0001009355,0.0002505682,0.003537718,0.0006684376,0.0003263427,0.0003788665,0.007952013],"category_scores_gemma":[0.0005072808,0.000169534,0.0001483542,0.0009428936,0.0004862026,0.0002615876,0.0005602132,0.0004380069,0.000491137],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.031288,"about_ca_system_score_gemma":0.06708016,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.991267,"about_ca_topic_score_gemma":0.9980828,"domain_scores_codex":[0.9997182,0.00001701278,0.000008420297,0.0000283218,0.0001065202,0.0001214076],"domain_scores_gemma":[0.999359,0.00002912113,0.00006522547,0.00001436978,0.0002500169,0.0002821603],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000638572,0.0003487362,0.4708524,0.0008480059,0.00004214558,0.006946274,0.01142955,0.002644868,0.01623126,0.01386977,0.212589,0.2635596],"study_design_scores_gemma":[0.00004823576,0.0001588333,0.6222369,0.0001762521,0.00001864289,0.0007060863,0.007847131,0.001266402,0.0009460993,0.0006999971,0.3658531,0.00004230502],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.793274,0.005135032,0.001251763,0.02573508,0.0003320139,0.0002787758,0.00702791,0.0002511583,0.1667142],"genre_scores_gemma":[0.8808151,0.005206541,0.001604957,0.001525864,0.00006094324,0.00007807488,0.001454147,0.00005513197,0.1091993],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.031288,"threshold_uncertainty_score":0.2270114,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02730610320510501,"score_gpt":0.2259910782543196,"score_spread":0.1986849750492146,"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."}}