{"id":"W3108766455","doi":"","title":"Comparison between the results of applications of the Canadian and Bhargava methods for irrigation water quality index at multi- locations in Tigris River. (A Case Study of Al-amarah Region)","year":2012,"lang":"en","type":"article","venue":"Maǧallaẗ ǧāmiʻaẗ Karbalāʼ/Maǧallaẗ ǧāmiʻaẗ karbalāʼ","topic":"Agricultural Economics and Practices","field":"Agricultural and Biological Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Index (typography); Quality (philosophy); Irrigation; Water quality; Water resource management; Hydrology (agriculture); Environmental science; Computer science; Geology; Ecology; World Wide Web; Geotechnical engineering; Biology; Physics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003065298,0.0003909251,0.0008001555,0.00008645579,0.0008666639,0.00006728232,0.0007736597,0.0002942225,0.00003156381],"category_scores_gemma":[0.0002790027,0.0001504524,0.0002190911,0.0006820473,0.0004475074,0.0003563024,0.0003490263,0.0003686853,0.000004843233],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002324811,"about_ca_system_score_gemma":0.00006297465,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.2190172,"about_ca_topic_score_gemma":0.5508757,"domain_scores_codex":[0.9956588,0.001104244,0.00167958,0.000592635,0.0003120644,0.0006527175],"domain_scores_gemma":[0.9954756,0.002127428,0.001221691,0.0004943029,0.0003902301,0.0002907319],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001629772,0.0008121409,0.9648095,0.00007431633,0.0002157892,0.000001664318,0.009719918,0.0001519384,0.005066121,0.0006557359,0.0008169452,0.01751294],"study_design_scores_gemma":[0.001171942,0.0002685705,0.9542565,0.00003488456,0.0001894002,0.00003650683,0.009172052,0.0006189639,0.00226864,0.0002957358,0.03128833,0.0003985192],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.991262,0.0004103456,0.0000761074,0.004254459,0.0001395661,0.002868664,0.0003525525,0.00002158123,0.0006146898],"genre_scores_gemma":[0.9982198,0.00004544224,0.0007406361,0.0001477028,0.000152611,0.000262886,0.0001413242,0.000007674346,0.0002818542],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3318585,"threshold_uncertainty_score":0.7861835,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1278624091555146,"score_gpt":0.3818750701261057,"score_spread":0.2540126609705911,"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."}}