{"id":"W2963891607","doi":"","title":"Gender and precarity","year":2016,"lang":"en","type":"article","venue":"","topic":"Employment and Welfare Studies","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Precarity; Diversity (politics); Event (particle physics); Gender diversity; Gender studies; Sociology; History; Business; Anthropology; Finance; Physics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001338693,0.0001231167,0.0002300981,0.0009519958,0.006908466,0.003355185,0.0002405426,0.001118931,0.01204057],"category_scores_gemma":[0.005026083,0.0001624095,0.00009912872,0.0009152906,0.00518878,0.000949115,0.002003473,0.002459715,0.0007974409],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00443807,"about_ca_system_score_gemma":0.003730795,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1675169,"about_ca_topic_score_gemma":0.4155114,"domain_scores_codex":[0.9990959,0.0002897129,0.00001832822,0.00007395646,0.0002422494,0.0002798743],"domain_scores_gemma":[0.9983605,0.0004761103,0.0001316363,0.00006902433,0.0002666448,0.0006961693],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0002473333,0.0001238343,0.07116701,0.0001850312,0.00002222052,0.0008177757,0.1731585,0.00007509239,0.0005475554,0.1016191,0.4802844,0.1717522],"study_design_scores_gemma":[0.00001023906,0.0000502486,0.1246381,0.0008910804,0.00001269317,0.0006199885,0.14524,0.0000361817,0.0002547261,0.01529996,0.7129144,0.00003248126],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2639818,0.05378972,0.0002982197,0.2230162,0.00375846,0.00002991413,0.0008362055,0.0000270559,0.4542624],"genre_scores_gemma":[0.8761941,0.01709283,0.0001804718,0.01195264,0.001090958,0.00002358734,0.0002420001,0.00003127689,0.09319203],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1675169,"threshold_uncertainty_score":0.3330837,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1340134404912212,"score_gpt":0.439890599017723,"score_spread":0.3058771585265018,"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."}}