{"id":"W6990212554","doi":"","title":"Crop rotation counts: Improves soil health","year":2020,"lang":"en","type":"other","venue":"The Atrium (University of Guelph)","topic":"Islamic Studies and History","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Ontario Agri-Food Innovation Alliance; Government of Ontario","keywords":"Crop; Crop rotation; Crop yield; Forage; Rotation (mathematics); Quality (philosophy); Soil quality","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.000360812,0.0002765157,0.0001552668,0.0002228517,0.0001969843,0.0002542136,0.0003804876,0.0002046489,0.03748637],"category_scores_gemma":[0.0009758417,0.00007374434,0.0001559162,0.0001961595,0.00008227389,0.0002273928,0.0003888243,0.0002156895,0.005366242],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002457249,"about_ca_system_score_gemma":0.0005135642,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00378862,"about_ca_topic_score_gemma":0.01431585,"domain_scores_codex":[0.9998941,0.00003599923,0.000004035914,0.00001678804,0.00002957375,0.00001944101],"domain_scores_gemma":[0.9996936,0.00003655017,0.0000580887,0.00002097329,0.00005000401,0.0001408348],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.002129447,0.002997504,0.019156,0.0002880036,0.00006163675,0.00006362432,0.00007480486,0.0001959023,0.006364444,0.0003958776,0.06852294,0.8997498],"study_design_scores_gemma":[0.00313396,0.01803733,0.7236531,0.0007153676,0.0003587948,0.0008480115,0.0004555929,0.002139445,0.01060763,0.002719668,0.237267,0.00006406632],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8445311,0.003937139,0.005100034,0.009154676,0.0006865398,0.0004879312,0.00597904,0.001975751,0.1281478],"genre_scores_gemma":[0.8866591,0.003728908,0.01791296,0.00238814,0.0003644465,0.0004626558,0.004797978,0.0001786119,0.08350724],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03748637,"threshold_uncertainty_score":0.1254044,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01763256366535268,"score_gpt":0.2400193226628485,"score_spread":0.2223867589974959,"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."}}