{"id":"W4411794229","doi":"10.1080/10807039.2025.2525828","title":"Ecological risk assessment and ecological restoration zoning based on nature-society-landscape systems: a case study of Hexi Corridor, Northwest China","year":2025,"lang":"en","type":"article","venue":"Human and Ecological Risk Assessment An International Journal","topic":"Land Use and Ecosystem Services","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Science North","funders":"National Natural Science Foundation of China","keywords":"Zoning; China; Restoration ecology; Geography; Ecology; Environmental resource management; Environmental planning; Environmental science; Biology; Archaeology; Civil engineering; Engineering","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":[0.0010404,0.0004058267,0.0002452523,0.001505184,0.001077762,0.0009959541,0.0008275585,0.0004825263,0.001043518],"category_scores_gemma":[0.001386213,0.0001671278,0.0005692987,0.002717679,0.000989732,0.0007596261,0.00112267,0.0004338773,0.00004939908],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004661329,"about_ca_system_score_gemma":0.002172708,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1541942,"about_ca_topic_score_gemma":0.23459,"domain_scores_codex":[0.9995097,0.0002117288,0.00002435676,0.00005374873,0.00007814192,0.000122308],"domain_scores_gemma":[0.9992631,0.0002412935,0.0001712822,0.00006512467,0.000108951,0.000150207],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000213496,0.0004425251,0.8729067,0.0001332548,0.0001519274,0.01092415,0.005295193,0.06537843,0.00109827,0.007958492,0.001418381,0.03407916],"study_design_scores_gemma":[0.0000446501,0.0002519502,0.7275565,0.00007396864,0.0001290788,0.001561625,0.03482015,0.2274324,0.0009026604,0.004053686,0.00309197,0.00008130469],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9978465,0.0000791632,0.000994891,0.0001259283,0.000002230342,0.00003330698,0.0001244574,0.000008995436,0.0007845488],"genre_scores_gemma":[0.997968,0.0001053274,0.001233581,0.000007087995,0.000001805644,0.00001664449,0.00010861,0.000002613064,0.0005563346],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1541942,"threshold_uncertainty_score":0.3065934,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01345336268200146,"score_gpt":0.3204183164439802,"score_spread":0.3069649537619787,"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."}}