{"id":"W6978058864","doi":"10.6084/m9.figshare.24892825.v1","title":"Additional file 1 of 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":"article","venue":"Figshare","topic":"Advanced Clustering Algorithms Research","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; Alberta Health Services","funders":"","keywords":"Colorectal cancer screening; Geospatial analysis; Cancer screening; Colorectal cancer; Data collection","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0009091404,0.0007401623,0.001070708,0.003081884,0.00267368,0.001312417,0.002110942,0.0007703588,0.3778607],"category_scores_gemma":[0.01190475,0.0006185223,0.0009012372,0.008644395,0.0004140666,0.0006969772,0.0007709295,0.0006581747,0.0125098],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007026206,"about_ca_system_score_gemma":0.01849795,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9152729,"about_ca_topic_score_gemma":0.9311249,"domain_scores_codex":[0.9993498,0.00006260023,0.00008877335,0.0001543881,0.0001719492,0.0001726137],"domain_scores_gemma":[0.9933277,0.002023122,0.0006932127,0.0005080173,0.0028782,0.0005697217],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0005726757,0.0003266649,0.1406941,0.00194715,0.0002317441,0.0002468333,0.0006465637,0.001043259,0.0001814205,0.001335245,0.8352245,0.0175498],"study_design_scores_gemma":[0.001802018,0.0002024343,0.807506,0.002609675,0.0004710059,0.0007845144,0.00372893,0.002717716,0.0003556572,0.002198365,0.1774381,0.0001855711],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.006329772,0.00004813591,0.0002351188,0.00008004115,0.00002553146,0.0002510873,0.9913898,0.00005428917,0.001586346],"genre_scores_gemma":[0.1256303,0.0004410695,0.00567796,0.0004391601,0.00006770951,0.00370044,0.8435383,0.0001778096,0.02032725],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3778607,"threshold_uncertainty_score":0.8874062,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04998991296728689,"score_gpt":0.3292026152227996,"score_spread":0.2792127022555128,"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."}}