{"id":"W4310147152","doi":"10.1007/s10668-022-02786-6","title":"Local perspectives on social-ecological transformation: China’s Sanjiangyuan National Park","year":2022,"lang":"en","type":"article","venue":"Environment Development and Sustainability","topic":"Land Use and Ecosystem Services","field":"Environmental Science","cited_by":13,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Government (linguistics); Livelihood; Psychological resilience; Ecological resilience; Geography; Natural resource; National park; Ecology; China; Environmental degradation; Economic growth; Natural resource economics; Development economics; Political science; Environmental resource management; Economics; Agriculture","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0007591418,0.0001625728,0.0001504322,0.00003206879,0.001209682,0.00002644879,0.0001526914,0.00004635905,0.006772025],"category_scores_gemma":[0.000009132931,0.0001382302,0.00004665881,0.0000963565,0.00009101129,0.0001613869,0.0002480083,0.0001695375,0.00006800921],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002110218,"about_ca_system_score_gemma":0.00004372486,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003071345,"about_ca_topic_score_gemma":0.00001718189,"domain_scores_codex":[0.9982883,0.0001465791,0.0002473973,0.0004051849,0.0006228161,0.0002897345],"domain_scores_gemma":[0.9997339,0.00003157397,0.00005754167,0.00009222579,0.000004847793,0.00007997132],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001060737,0.00684949,0.4616035,0.0003695067,0.0002498974,0.0001060437,0.2641568,0.08287123,0.00004488467,0.01519002,0.006921246,0.1605767],"study_design_scores_gemma":[0.000428968,0.0001137047,0.8635227,0.000001002855,0.000005666097,0.000004744886,0.02114538,0.0007478073,0.00003854552,0.002174244,0.1115615,0.0002557623],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.988968,0.00003640342,0.0002764106,0.003256103,0.00003242706,0.0003841466,0.000007923268,0.00003383456,0.007004775],"genre_scores_gemma":[0.9992129,0.00001257679,0.000100141,0.0002014625,0.00001863151,0.0002021955,0.00003179252,0.000007122614,0.0002131507],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4019192,"threshold_uncertainty_score":0.9941359,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008939562822554604,"score_gpt":0.2141956645104829,"score_spread":0.2052561016879283,"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."}}