{"id":"W7164926853","doi":"10.1080/17153379.2018.12557907","title":"Rural China on the Eve of Revolution: Sichuan Fieldnotes, 1949–1950.","year":2018,"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":"China; Rural area; Rural development; Rural population","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":[0.001056286,0.0003278605,0.0002064069,0.001934257,0.008151984,0.002459952,0.0005245986,0.001105419,0.00532325],"category_scores_gemma":[0.001295347,0.0001718767,0.0001509638,0.005752292,0.004014562,0.001680962,0.001751514,0.001475208,0.0001522427],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008312677,"about_ca_system_score_gemma":0.006387461,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1643226,"about_ca_topic_score_gemma":0.3917978,"domain_scores_codex":[0.9996686,0.00009076894,0.000009915423,0.00002929877,0.00004527741,0.0001561124],"domain_scores_gemma":[0.9995907,0.0002286297,0.0000451814,0.00002445902,0.000043873,0.00006722393],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0004348185,0.00008426094,0.0219061,0.000942421,0.00006895376,0.003039466,0.3983544,0.0005517571,0.001164758,0.3465539,0.1430122,0.08388697],"study_design_scores_gemma":[0.00002137672,0.00006162626,0.1887809,0.0005434387,0.00003245494,0.0001226307,0.1099142,0.0001227341,0.0007830892,0.008833862,0.6907504,0.00003317557],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.63342,0.05489134,0.0003752046,0.03460402,0.002339962,0.0001019394,0.0009959169,0.00003816666,0.2732334],"genre_scores_gemma":[0.921123,0.008767786,0.00008246433,0.001702847,0.0006771661,0.00004626986,0.0001872393,0.0000116022,0.06740168],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1643226,"threshold_uncertainty_score":0.3267323,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01975992461342525,"score_gpt":0.2589972762550589,"score_spread":0.2392373516416336,"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."}}