{"id":"W4313466203","doi":"10.3390/ijerph20010019","title":"How Can Quantitative Analysis Be Used to Improve Occupational Health without Reinforcing Social Inequalities? An Examination of Statistical Methods","year":2022,"lang":"en","type":"review","venue":"International Journal of Environmental Research and Public Health","topic":"Workplace Health and Well-being","field":"Health Professions","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal; Université du Québec en Outaouais","funders":"Fonds de Recherche du Québec-Société et Culture","keywords":"Occupational safety and health; Psychology; Confounding; Affect (linguistics); Population; Identification (biology); Poison control; Environmental health; Medicine","routes":{"ca_aff":true,"ca_fund":true,"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":["metaresearch","metaepi_narrow","sts","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.03108417,0.0003371754,0.002017075,0.002846409,0.001393357,0.0001242371,0.0007071302,0.000237692,0.0008297556],"category_scores_gemma":[0.002580838,0.0002990534,0.0002688761,0.0009441039,0.0002646601,0.0004806187,0.0004869902,0.002669562,0.000002718908],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.004819854,"about_ca_system_score_gemma":0.008563756,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001062997,"about_ca_topic_score_gemma":0.0004901906,"domain_scores_codex":[0.9773322,0.01512241,0.002672447,0.0005099509,0.003141018,0.001221995],"domain_scores_gemma":[0.9885713,0.006229758,0.003063646,0.0002444143,0.0003998227,0.001491024],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001756873,0.0003255483,0.0009214097,0.002871166,0.0008014903,0.00000936934,0.01163454,0.000002821276,0.000001707987,0.009698302,0.0004103069,0.9731476],"study_design_scores_gemma":[0.001154249,0.004274486,0.008684359,0.001297312,0.0001257407,0.00002019308,0.0309758,0.0001779206,3.38269e-7,0.0004450877,0.9525018,0.0003427131],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.01504533,0.7770198,0.1085363,0.06817075,0.003404064,0.008998564,0.01803078,0.0000595734,0.0007348236],"genre_scores_gemma":[0.02800937,0.9505997,0.01503844,0.00160256,0.0009308662,0.000258092,0.002948218,0.00008793396,0.0005248345],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.972805,"threshold_uncertainty_score":0.9999462,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3877318856522147,"score_gpt":0.610096290046397,"score_spread":0.2223644043941823,"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."}}