{"id":"W7164880984","doi":"10.1080/17153379.2015.12557381","title":"Spying for the People: Mao’s Secret Agents, 1949–1967.","year":2015,"lang":"en","type":"article","venue":"Pacific Affairs","topic":"Chinese history and philosophy","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Espionage; Industrial espionage; Subpoena","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":[0.0007242033,0.0002779382,0.0001396826,0.0006578464,0.008095449,0.001583086,0.000360761,0.0009441336,0.003700763],"category_scores_gemma":[0.001325575,0.000180922,0.0001161725,0.0009899589,0.006901419,0.002190861,0.001424658,0.001951433,0.0001968651],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006858283,"about_ca_system_score_gemma":0.004888975,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1122414,"about_ca_topic_score_gemma":0.2703171,"domain_scores_codex":[0.9997161,0.00009994137,0.000009663291,0.0000286348,0.00004110871,0.0001045669],"domain_scores_gemma":[0.9997792,0.00009672112,0.00003853183,0.00001793134,0.00002910513,0.00003865889],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008620476,0.0000277278,0.007698317,0.000163407,0.00001918192,0.0009877578,0.5549173,0.000163091,0.0003459762,0.3676142,0.02078715,0.04718974],"study_design_scores_gemma":[0.00002553064,0.00008694456,0.08103944,0.0006608615,0.00004376164,0.0005501953,0.185437,0.0003467903,0.0009251137,0.03839953,0.692442,0.00004273059],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5687799,0.03515867,0.0006697149,0.03473885,0.0006729866,0.00005722718,0.0001703173,0.0000219561,0.3597305],"genre_scores_gemma":[0.9502392,0.005255892,0.0001222196,0.0007094846,0.0001227299,0.00001702653,0.00002265918,0.000006902137,0.04350391],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1122414,"threshold_uncertainty_score":0.2231762,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06347750954555442,"score_gpt":0.3005703587232707,"score_spread":0.2370928491777163,"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."}}