{"id":"W6922237701","doi":"10.11575/prism/42670","title":"Geospatial analysis and participant characteristics associated with colorectal cancer screening participation in Alberta, Canada: a population-based cross-sectional study","year":2023,"lang":"en","type":"other","venue":"University of Calgary","topic":"Mathematics Education and Programs","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Colorectal cancer; Logistic regression; Colorectal cancer screening; Geospatial analysis; Cancer registry; Multinomial logistic regression; Electronic health record","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002228713,0.0001463368,0.0004522583,0.000267607,0.00007128641,0.00001704939,0.00007913425,0.0001236554,0.0005975699],"category_scores_gemma":[0.0002280902,0.0001553312,0.00004751014,0.0004359544,0.00004497751,0.00002385435,0.00002386017,0.0001218784,6.041448e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001648605,"about_ca_system_score_gemma":0.0004132529,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9096891,"about_ca_topic_score_gemma":0.9965781,"domain_scores_codex":[0.9989388,0.00009932707,0.0002646482,0.0002151011,0.0003195621,0.0001625639],"domain_scores_gemma":[0.9987754,0.000467577,0.0004812652,0.0001194746,0.00008359759,0.00007275135],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005715345,0.0002628374,0.9974647,0.0000593195,0.0007852352,0.00001007179,0.0006948095,0.00005240885,1.140006e-7,0.00009317441,0.0003068241,0.0002134229],"study_design_scores_gemma":[0.0006309296,0.0000485408,0.9874793,0.000108941,0.0008130076,9.140329e-8,0.0001478636,0.01049405,5.619726e-7,0.00002726328,0.00008823107,0.0001611887],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9971105,0.000004805368,0.001075877,0.00002016897,0.00006831728,0.0005228683,0.0001123994,0.00006285468,0.001022151],"genre_scores_gemma":[0.9827527,0.000002449741,0.0006062,0.000007104781,0.00001751329,0.000008159634,0.0002507195,0.00008623398,0.01626889],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08688904,"threshold_uncertainty_score":0.6542971,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04144251898994521,"score_gpt":0.3064271805220167,"score_spread":0.2649846615320715,"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."}}