{"id":"W2388868774","doi":"","title":"Forest health evaluation for tending of recreational forest in Xishan Forest Farm in Beijing city","year":2014,"lang":"en","type":"article","venue":"Zhongnan Linye Keji Daxue xuebao","topic":"Advanced Decision-Making Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"L'Alliance Boviteq","funders":"","keywords":"Robinia; Beijing; Agroforestry; Forest management; Tree health; Recreation; Thinning; Forest health; Forestry; Urban forest; Pruning; Forest farming; Forest restoration; Environmental science; Forest ecology; Geography; China; Ecology; Ecosystem; Biology; Agronomy","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":[0.0004154391,0.0003086993,0.0002218616,0.0009231349,0.0005526975,0.0002621626,0.0002164794,0.000240299,0.001126333],"category_scores_gemma":[0.0002983021,0.000117496,0.0003391712,0.0006998075,0.0002234208,0.0002372832,0.0003097166,0.0001608262,0.0001109776],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009817156,"about_ca_system_score_gemma":0.0007074353,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04382631,"about_ca_topic_score_gemma":0.1218597,"domain_scores_codex":[0.99979,0.0000345621,0.00002060805,0.00003586227,0.00006859258,0.00005032497],"domain_scores_gemma":[0.9996942,0.00001535137,0.00005305346,0.00001355842,0.0001374509,0.0000864059],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001841578,0.0001941723,0.9779245,0.0001009368,0.00005086262,0.0003591832,0.0008770159,0.000621882,0.002848503,0.0000457697,0.0005639652,0.01622905],"study_design_scores_gemma":[0.000004517856,0.0001519412,0.9978769,0.000006350083,0.00001815003,0.00005243203,0.0008664206,0.0004280563,0.0002439149,0.00001003656,0.0003364527,0.000004894891],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9988962,0.00008469415,0.0001178742,0.00002553807,0.000002653211,0.00003496824,0.0002860547,0.000006346115,0.0005456703],"genre_scores_gemma":[0.9981714,0.00008914017,0.0002846963,0.00002200064,0.000003412611,0.00002953471,0.0005849818,0.000001604298,0.0008130801],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04382631,"threshold_uncertainty_score":0.08714241,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05325355867242984,"score_gpt":0.3666981425687578,"score_spread":0.313444583896328,"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."}}