{"id":"W4206789032","doi":"10.1093/annweh/wxab104","title":"Exposure Determinants in the French Database COLCHIC (1987–2019): Statistical Modeling across 77 Chemicals","year":2021,"lang":"en","type":"article","venue":"Annals of Work Exposures and Health","topic":"Occupational exposure and asthma","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Collège de Maisonneuve; Institut de recherche Robert-Sauvé en santé et en sécurité du travail","funders":"Institut National de Recherche et de Sécurité","keywords":"Personal protective equipment; Sample (material); Tobit model; Exposure assessment; Toxicology; Environmental health; Statistics; Database; Medicine; Demography; Computer science; Chemistry; Coronavirus disease 2019 (COVID-19); Mathematics; Biology; Pathology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02087397,0.001200477,0.002254215,0.004156988,0.0006197976,0.002107083,0.00240661,0.001663648,0.005353512],"category_scores_gemma":[0.03013653,0.000793866,0.006508433,0.006833932,0.0005335568,0.000514868,0.001379853,0.001206007,0.0008147629],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007591666,"about_ca_system_score_gemma":0.006005127,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.5153928,"about_ca_topic_score_gemma":0.2259565,"domain_scores_codex":[0.9874371,0.008426284,0.0007468792,0.001878149,0.0008879757,0.0006235826],"domain_scores_gemma":[0.9690115,0.02169061,0.003811459,0.002136918,0.002906485,0.0004430065],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002542864,0.0002245072,0.7281625,0.00238086,0.02447347,0.001046198,0.0005329461,0.1597186,0.0004431267,0.004964332,0.03673247,0.03877804],"study_design_scores_gemma":[0.001085022,0.0007812246,0.680867,0.001237658,0.01318707,0.0007359739,0.0007093516,0.2367765,0.0005889937,0.002645256,0.06119233,0.000193646],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6431965,0.04385029,0.02634486,0.005153758,0.0003188874,0.001020093,0.2743121,0.001001251,0.004802196],"genre_scores_gemma":[0.8824855,0.005922811,0.01556206,0.0008416406,0.000138486,0.001707661,0.08943123,0.0001398661,0.003770706],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5153928,"threshold_uncertainty_score":0.9749224,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.117429760534546,"score_gpt":0.4328012616974092,"score_spread":0.3153715011628632,"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."}}