{"id":"W7010568788","doi":"","title":"Intimacy, casualization and the formation of metis in a mobile era: a study of married female migrants in Shenzhen, China","year":2019,"lang":"en","type":"article","venue":"CUHK Digital Repository (Chinese University of Hong Kong)","topic":"China's Global Influence and Migration","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Metis; China; Population; Immigration; Ethnic group","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002154861,0.00008148164,0.000249586,0.00014913,0.00008890688,0.00002943927,0.0001701946,0.00005237965,0.000003580194],"category_scores_gemma":[0.00009644544,0.0000696935,0.00005273718,0.0004703056,0.0002306575,0.001087363,0.00007144342,0.00006653623,8.180889e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006495983,"about_ca_system_score_gemma":0.00006184416,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0136281,"about_ca_topic_score_gemma":0.01363912,"domain_scores_codex":[0.9990984,0.0001459558,0.000264874,0.000139608,0.0002544654,0.00009674844],"domain_scores_gemma":[0.9993995,0.00008666566,0.0002473581,0.0001402879,0.00009853801,0.00002759835],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003435436,0.000314838,0.8912214,0.00005570416,0.00001546276,0.000006388985,0.1052488,0.0004830024,0.0009091308,0.0003391549,0.00001454331,0.001048015],"study_design_scores_gemma":[0.002954986,0.0002474608,0.916419,0.0001303427,0.0000238921,0.000002436851,0.0784824,0.0009702915,0.0001965076,0.0004009211,0.00005491878,0.0001168334],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9944079,0.0001208177,0.00002465108,0.00001274775,0.00005585297,0.0007205303,0.000007794805,0.000008399717,0.004641308],"genre_scores_gemma":[0.9997295,0.00003833175,0.0000107804,0.000002272388,0.000006158906,8.299389e-7,0.000005085168,0.000002863426,0.0002042065],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02676644,"threshold_uncertainty_score":0.9929402,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00482225805800406,"score_gpt":0.2352245273373803,"score_spread":0.2304022692793762,"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."}}