{"id":"W7164937690","doi":"10.1080/17153379.2015.12557271","title":"Taming Tibet: Landscape Transformation and the Gift of Chinese Development. Studies of the Weatherhead East Asian Institute, Columbia University.","year":2015,"lang":"en","type":"article","venue":"Pacific Affairs","topic":"China's Ethnic Minorities and Relations","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"East Asia; Transformation (genetics); China; Asian studies","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.0006772055,0.0001580171,0.00008292512,0.000414282,0.002533682,0.00169411,0.0002551253,0.0003331409,0.004184675],"category_scores_gemma":[0.0008404852,0.00007273987,0.00006408939,0.001085967,0.003135149,0.001137641,0.0008048088,0.0005973015,0.00008441696],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00217867,"about_ca_system_score_gemma":0.002685481,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0641293,"about_ca_topic_score_gemma":0.174621,"domain_scores_codex":[0.9998779,0.00005883743,0.000003068427,0.000005072817,0.00001436956,0.00004061806],"domain_scores_gemma":[0.9997125,0.00007101012,0.00003807998,0.00001509205,0.00002493731,0.0001383147],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001968771,0.0001644795,0.1030463,0.0001999086,0.00002352315,0.001742201,0.3691531,0.0003916199,0.00136889,0.3979284,0.01672145,0.1090633],"study_design_scores_gemma":[0.00008672569,0.0001519153,0.3549367,0.0003217215,0.00004403561,0.0005142305,0.4514,0.0009019946,0.0006953921,0.04351563,0.1473909,0.00004088494],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"other","genre_scores_codex":[0.8815752,0.004750546,0.0001636963,0.01460365,0.0001055441,0.00001381889,0.00006735628,0.0000102225,0.09871],"genre_scores_gemma":[0.9950927,0.0007018759,0.00003462425,0.0001122629,0.000007957192,0.000002517556,0.000008069144,9.426433e-7,0.004038983],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.0641293,"threshold_uncertainty_score":0.127512,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.025937996438624,"score_gpt":0.2560322867761975,"score_spread":0.2300942903375735,"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."}}