{"id":"W3005590523","doi":"10.1139/cjss2012-079","title":"Generation of soil drainage equations from an artificial neural network-analysis approach","year":2013,"lang":"en","type":"article","venue":"BioOne Complete (BioOne)","topic":"Soil and Unsaturated Flow","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Drainage; Hydrology (agriculture); Topographic Wetness Index; Soil science; Environmental science; Soil water; Watershed; Mean squared error; Digital elevation model; Geology; Geotechnical engineering; Mathematics; Statistics; Remote sensing; Ecology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005026445,0.0006723769,0.0003960149,0.0007923394,0.0002543964,0.0004919584,0.0006513843,0.000573148,0.001766492],"category_scores_gemma":[0.001951253,0.0005090231,0.0006569283,0.0008849532,0.0001698531,0.0004502271,0.0004541631,0.0007055142,0.0003269332],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008393016,"about_ca_system_score_gemma":0.0008711822,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01269282,"about_ca_topic_score_gemma":0.01579774,"domain_scores_codex":[0.9998379,0.00004036078,0.00002124883,0.00004594389,0.00004097827,0.00001352969],"domain_scores_gemma":[0.9994124,0.0002838274,0.00005790335,0.0000274803,0.0002057003,0.00001261244],"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":[0.0000197727,0.0000305802,0.002264553,0.00003774173,0.00003203268,0.00004751699,0.00003403655,0.96457,0.002382198,0.001328559,0.0003472809,0.02890573],"study_design_scores_gemma":[0.000002141758,0.000003852411,0.0001879809,0.000001789345,0.000003221175,0.000002391273,0.000002815325,0.9989277,0.0003641787,0.0003321902,0.0001695406,0.000002305242],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0913443,0.00007164278,0.9046865,0.00007437348,0.00003319444,0.0001558786,0.0004087258,0.000852121,0.002373277],"genre_scores_gemma":[0.6015556,0.0001651994,0.3930549,0.00005666579,0.0000191651,0.0006379122,0.001108171,0.0001528232,0.00324952],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01269282,"threshold_uncertainty_score":0.02523786,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3107153788708134,"score_gpt":0.2398635474369871,"score_spread":0.07085183143382628,"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."}}