{"id":"W4409524273","doi":"10.1016/j.gecco.2025.e03595","title":"Effectively managed Northeast China Tiger and Leopard National Park by regulating Korean pine seed collection","year":2025,"lang":"en","type":"article","venue":"Global Ecology and Conservation","topic":"Ecology and Conservation Studies","field":"Agricultural and Biological Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Key Research and Development Program of China; Ministry of Science and Technology of the People's Republic of China","keywords":"Tiger; China; Geography; Leopard; National park; Forestry; Environmental protection; Agroforestry; Archaeology; Ecology; Biology","routes":{"ca_aff":false,"ca_fund":false,"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":[0.0005148452,0.000256988,0.0001070192,0.0004373407,0.0006578201,0.0008751441,0.0007087678,0.0002267139,0.001130924],"category_scores_gemma":[0.0006250559,0.00008469353,0.0001825061,0.0004150674,0.000537972,0.0009069122,0.001017247,0.000261617,0.00008767238],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00118713,"about_ca_system_score_gemma":0.003215533,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02079483,"about_ca_topic_score_gemma":0.0828968,"domain_scores_codex":[0.9997684,0.0000602871,0.00001238867,0.00004812098,0.00003808894,0.00007265323],"domain_scores_gemma":[0.9997016,0.00003509058,0.00007488025,0.00003837383,0.00006767343,0.00008240998],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002320368,0.0006855144,0.5936584,0.0006170841,0.0001447035,0.001014142,0.003797214,0.07555538,0.03312096,0.02112333,0.006548801,0.2635024],"study_design_scores_gemma":[0.0001337693,0.0006287331,0.7548026,0.0002768797,0.0002697474,0.0004035055,0.01419307,0.1610079,0.01056882,0.009809318,0.04774562,0.0001598584],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.974654,0.0003103661,0.01506027,0.0004458105,0.00002815,0.0002152798,0.0001978124,0.0001182406,0.008970022],"genre_scores_gemma":[0.9933374,0.0001264336,0.005615343,0.00005092414,0.000003826591,0.00008832043,0.0001054183,0.000006736307,0.0006656179],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02079483,"threshold_uncertainty_score":0.04134762,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007823096333541805,"score_gpt":0.2173482938743404,"score_spread":0.2095251975407986,"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."}}