{"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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002148023,0.00006884646,0.0000689107,0.000007321558,0.0001174545,0.00009528807,0.0001216794,0.00003968415,0.00157979],"category_scores_gemma":[0.00001071045,0.00002668445,0.00002483507,0.0001516314,0.00004399841,0.0002369064,0.00004161196,0.00007740418,0.0003747497],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005903758,"about_ca_system_score_gemma":0.00000786909,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.06429137,"about_ca_topic_score_gemma":0.5090132,"domain_scores_codex":[0.9993593,0.00003544571,0.0001401712,0.0001756353,0.0001175843,0.0001719159],"domain_scores_gemma":[0.9997884,0.00002685074,0.00005928711,0.00004374403,0.00004420501,0.00003748432],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001778778,0.0004885072,0.5909295,0.0000177393,0.00004279935,0.00003507207,0.006806976,0.00005625311,0.1227721,0.01460723,0.01118011,0.2528858],"study_design_scores_gemma":[0.00008980865,0.00009412818,0.7971036,0.000008737791,0.000003873197,7.748506e-7,0.0001395757,0.00006398855,0.002547361,0.002974208,0.1968797,0.00009419757],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9656969,0.00001024479,0.000005245336,0.001664721,0.0001829007,0.0001080344,0.000001116437,0.00002868156,0.03230217],"genre_scores_gemma":[0.9929901,0.000002097089,0.0001341637,0.0004309852,0.000113053,0.000006380293,0.00002914226,4.403693e-7,0.006293661],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4447218,"threshold_uncertainty_score":0.9993329,"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."}}