{"id":"W3211083032","doi":"10.1136/oem-2021-epi.275","title":"P-336 Gender differences in occupational exposure in the Canadian job-exposure-matrix (CANJEM)","year":2021,"lang":"en","type":"article","venue":"Poster presentations","topic":"Health, Environment, Cognitive Aging","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre Hospitalier de l’Université de Montréal","funders":"","keywords":"Confidence interval; Job-exposure matrix; Statistics; Computer science; Econometrics; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004089985,0.0001350604,0.0001199068,0.0001116953,0.0002530271,0.0000976177,0.0002587037,0.00007344536,0.002545718],"category_scores_gemma":[0.0001244176,0.0001186,0.00003954572,0.0004649784,0.0001212527,0.0003114217,0.00009470898,0.0002848881,0.0003699388],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002844345,"about_ca_system_score_gemma":0.0001782531,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.09892051,"about_ca_topic_score_gemma":0.7636877,"domain_scores_codex":[0.9978983,0.0005023319,0.0003109313,0.0004112781,0.0004572324,0.0004199402],"domain_scores_gemma":[0.999221,0.0002589528,0.00005314953,0.0003122067,0.00001176619,0.0001429326],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000003309067,0.00005892878,0.9924793,0.000004694962,0.000004231572,0.00006212682,0.005734403,0.0002873189,0.0002042684,0.0001273999,0.0004212545,0.0006127701],"study_design_scores_gemma":[0.0003540825,0.00001443501,0.995687,0.000007716263,0.000007083889,0.00001673932,0.001789181,0.0001668795,0.00007405846,0.0007187309,0.001030987,0.0001331073],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.973358,0.00008620445,0.0001720583,0.004521152,0.0001017398,0.0004416179,0.00006176552,0.000009238697,0.02124828],"genre_scores_gemma":[0.9969227,0.00002272463,0.0003714105,0.001984838,0.00004189344,0.0001122825,0.00008310677,0.0000116175,0.0004494022],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6647671,"threshold_uncertainty_score":0.9983661,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05683086002947785,"score_gpt":0.3138190308855666,"score_spread":0.2569881708560888,"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."}}