{"id":"W176800414","doi":"10.1007/s10354-006-0340-3","title":"\"A heart for Vienna\" – The prevention program for the big city. Blue-collar workers as a special target group","year":2006,"lang":"en","type":"article","venue":"Wiener Medizinische Wochenschrift","topic":"Workplace Health and Well-being","field":"Health Professions","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Medicine; Overweight; Obesity; Abdominal obesity; Blue collar; Population; Environmental health; Risk factor; Disease; Gerontology; Physical therapy; Demography; Metabolic syndrome; Internal medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.004585171,0.0004649907,0.0005711181,0.0001290898,0.003967195,0.00008454709,0.0006095218,0.0005698744,0.0002449143],"category_scores_gemma":[0.0008804005,0.0002813052,0.0004777305,0.0006867591,0.0003005268,0.0001717424,0.0001532431,0.001087228,0.0001510049],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008077336,"about_ca_system_score_gemma":0.001054624,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003781961,"about_ca_topic_score_gemma":0.001221206,"domain_scores_codex":[0.9948544,0.0007169115,0.001175596,0.0007241462,0.0006567425,0.001872206],"domain_scores_gemma":[0.9946156,0.003355572,0.0005353875,0.000827534,0.0003417941,0.0003240967],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002965751,0.000955343,0.02185833,0.001065151,0.0002775347,0.000005002015,0.007700214,0.0002002314,0.0007163531,0.0810645,0.847513,0.03567858],"study_design_scores_gemma":[0.002958164,0.00060467,0.003815636,0.0003101297,0.000163273,0.00000510766,0.003433131,0.0005945183,0.0002004071,0.007316569,0.9802501,0.0003483289],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4641216,0.01112622,0.0566243,0.2274752,0.04684922,0.1020774,0.0003335632,0.002290057,0.0891025],"genre_scores_gemma":[0.7710809,0.0002217993,0.0424277,0.02199182,0.08007294,0.04815819,0.0007786287,0.0004601909,0.03480785],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3069593,"threshold_uncertainty_score":0.9999639,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03334406756006151,"score_gpt":0.3761524075283522,"score_spread":0.3428083399682907,"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."}}