{"id":"W4409413757","doi":"10.69622/28263536.v1","title":"Non-standard employment and health : exploring the pathways to health inequality","year":2025,"lang":"en","type":"preprint","venue":"","topic":"Employment and Welfare Studies","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Inequality; Health equity; Labour economics; Economics; Economic growth; Health care; Mathematics","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":[0.006848615,0.0002808507,0.0004909383,0.001801447,0.001820859,0.004831913,0.001326002,0.001257681,0.006851246],"category_scores_gemma":[0.01304946,0.0002989609,0.001254485,0.002793211,0.003842016,0.004452347,0.005909223,0.002233208,0.0003900738],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002207681,"about_ca_system_score_gemma":0.004242985,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01874345,"about_ca_topic_score_gemma":0.01953652,"domain_scores_codex":[0.9961204,0.002370317,0.0001350619,0.0004175759,0.0003328546,0.0006238295],"domain_scores_gemma":[0.9886867,0.007820357,0.001790527,0.0004651702,0.0005152457,0.0007219257],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002287543,0.0003673142,0.797857,0.00112128,0.0005432473,0.0004185457,0.03318201,0.001095088,0.0001805702,0.08963449,0.003799672,0.0715721],"study_design_scores_gemma":[0.00003594581,0.0003346301,0.8454768,0.003134181,0.0003144861,0.0002360213,0.06884035,0.004410968,0.0002590019,0.06531366,0.01157368,0.00007021746],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9210167,0.01983895,0.004034711,0.03683494,0.0002438133,0.0001786663,0.000906125,0.00001766026,0.01692846],"genre_scores_gemma":[0.9915575,0.005161119,0.001152136,0.001054419,0.0001057361,0.0001454966,0.0001510206,0.000007375366,0.000665069],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01874345,"threshold_uncertainty_score":0.0372687,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.295955648140988,"score_gpt":0.4773634853541066,"score_spread":0.1814078372131186,"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."}}