{"id":"W1565107572","doi":"10.1002/047147844x.aw1506","title":"Water Logging: Topographic and Agricultural Impacts","year":2004,"lang":"en","type":"other","venue":"Water Encyclopedia","topic":"Irrigation Practices and Water Management","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Soil water; Ponding; Water table; Hydrology (agriculture); Environmental science; Soil science; Snowmelt; Surface runoff; Geology; Logging; Surface water; Groundwater; Snow; Geotechnical engineering; Geomorphology; Drainage; Environmental engineering; Forestry","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000106201,0.0001475602,0.00006181833,0.001074285,0.0002951506,0.000992364,0.0001374405,0.0001015399,0.01748141],"category_scores_gemma":[0.0006187358,0.00004536429,0.00008060618,0.003033401,0.0002137811,0.000499174,0.0005216681,0.0001290464,0.0008700059],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004267321,"about_ca_system_score_gemma":0.000389465,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02248698,"about_ca_topic_score_gemma":0.05291598,"domain_scores_codex":[0.9998721,0.00003249506,0.000006048146,0.000007578366,0.00005013193,0.0000315743],"domain_scores_gemma":[0.9996825,0.00004933175,0.0000918824,0.000009607293,0.0001090348,0.00005760776],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001562737,0.000356258,0.6259831,0.0003078549,0.00005829502,0.001813301,0.0005091518,0.004573539,0.0009729746,0.002585376,0.01938316,0.3433007],"study_design_scores_gemma":[0.0000100265,0.0001084642,0.9678993,0.0001382949,0.00002523139,0.0006871744,0.002883203,0.001225678,0.0002962271,0.001436021,0.02527763,0.00001275912],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"other","genre_scores_codex":[0.8756402,0.003872332,0.000214354,0.001393242,0.00007495212,0.00005513714,0.00398377,0.0000550827,0.1147109],"genre_scores_gemma":[0.9904088,0.002857788,0.00007309602,0.00006843304,0.00003928842,0.000005836463,0.0008120501,0.000005991372,0.005728638],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.02248698,"threshold_uncertainty_score":0.05848116,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00867619019859011,"score_gpt":0.1985793561333626,"score_spread":0.1899031659347725,"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."}}