{"id":"W1464652869","doi":"","title":"Afforesting former agricultural lands with high value hardwoods in southern Ontario.","year":2009,"lang":"en","type":"article","venue":"MOspace Institutional Repository (University of Missouri)","topic":"Invertebrate Taxonomy and Ecology","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Ministry of Natural Resources","keywords":"Agriculture; Forestry; Value (mathematics); Geography; Agroforestry; Agricultural economics; Environmental science; Archaeology; Economics; Mathematics","routes":{"ca_aff":false,"ca_fund":true,"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":[0.0001116915,0.000169376,0.0001472303,0.0004370785,0.003323412,0.0007735448,0.0003313216,0.0002023643,0.002733134],"category_scores_gemma":[0.0003545163,0.0001414768,0.0001064592,0.00122132,0.0006540203,0.0002883674,0.0005858707,0.0002459471,0.0002734254],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01476896,"about_ca_system_score_gemma":0.01699488,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9905714,"about_ca_topic_score_gemma":0.9991209,"domain_scores_codex":[0.9998237,0.000008894578,0.000004797743,0.00002447459,0.00005143569,0.00008670222],"domain_scores_gemma":[0.9997593,0.00001197679,0.00004913167,0.00000746943,0.00008135545,0.00009075042],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002844047,0.00008857506,0.8875672,0.0002902958,0.00004520815,0.002298318,0.02628118,0.0003603131,0.006462606,0.001595296,0.02006241,0.05466407],"study_design_scores_gemma":[0.000005874484,0.0000166629,0.9709995,0.00003257522,0.000009850039,0.0001110826,0.01375657,0.0001158664,0.0001571609,0.00008676053,0.01470201,0.000006013977],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9812481,0.000823217,0.000085389,0.0008198868,0.00002940694,0.00005493897,0.00166251,0.000009656919,0.01526688],"genre_scores_gemma":[0.9759972,0.0009075928,0.0002568204,0.0001622102,0.000009585952,0.00002115796,0.0008832442,0.000004655764,0.02175758],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01476896,"threshold_uncertainty_score":0.1071568,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00860552267547927,"score_gpt":0.1498674698697308,"score_spread":0.1412619471942516,"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."}}