{"id":"W4281723865","doi":"10.1017/wsc.2022.28","title":"The importance of species selection in cover crop mixture design","year":2022,"lang":"en","type":"article","venue":"Weed Science","topic":"Ecology and Vegetation Dynamics Studies","field":"Environmental Science","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"Agriculture and Agri-Food Canada","keywords":"Monoculture; Weed; Species richness; Agronomy; Cover crop; Biology; Species evenness; Biomass (ecology); Agroecosystem; Species diversity; Sorghum; Crop; Crop diversity; Weed control; Agriculture; Ecology","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.001090184,0.00004114566,0.00005183529,0.00002890283,0.0009022071,0.00001077271,0.0002996889,0.0000101086,0.0004643828],"category_scores_gemma":[0.0001114366,0.00003092213,0.00001264486,0.0008716387,0.0008672734,0.0001227242,0.0002094595,0.0001065593,0.00001813278],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001845898,"about_ca_system_score_gemma":0.00003368336,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008232309,"about_ca_topic_score_gemma":0.0007634076,"domain_scores_codex":[0.999232,0.00005966042,0.0001153269,0.0001618639,0.0002670216,0.0001641305],"domain_scores_gemma":[0.9997199,0.0001091905,0.00007345295,0.0000736693,0.000008715383,0.00001508598],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000297433,0.00005855795,0.6373598,0.000001515379,0.000002866838,0.000002312587,0.001415491,0.1581911,0.1956767,0.004868157,0.002092841,0.0003009147],"study_design_scores_gemma":[0.00008276402,0.00005992912,0.9770274,6.847769e-7,0.00000135178,0.000003292751,0.0002990141,0.0171561,0.001069071,0.002210639,0.002039501,0.00005021889],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9866163,0.00005418546,0.001015292,0.0005807524,0.0001434172,0.0001768182,0.000001431638,0.000009025734,0.01140279],"genre_scores_gemma":[0.996851,0.000003680314,0.0004738332,0.0001375249,0.000003661892,0.00003592456,1.489842e-7,0.000001591322,0.002492662],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3396676,"threshold_uncertainty_score":0.6939139,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0115091496628343,"score_gpt":0.2266386918143513,"score_spread":0.2151295421515169,"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."}}