{"id":"W2062644281","doi":"10.1109/hicss.2012.316","title":"Improving Colon Cancer Screening Levels Using Self-Serve Technologies: The Case of the Incomplete Appointment","year":2012,"lang":"en","type":"article","venue":"","topic":"Colorectal Cancer Screening and Detection","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Portfolio; Context (archaeology); Phone; Knowledge management; Work (physics); Computer science; Risk analysis (engineering); Action (physics); Service (business); Process management; Key (lock); Business; Marketing; Engineering; Computer security","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":[0.003166825,0.0004202306,0.0004157594,0.001468816,0.003653498,0.002142743,0.001236862,0.002840896,0.005349859],"category_scores_gemma":[0.01720169,0.0003509541,0.0006526993,0.001368818,0.001530062,0.001728072,0.00168534,0.001697364,0.0006136067],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002372322,"about_ca_system_score_gemma":0.002048591,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006822914,"about_ca_topic_score_gemma":0.01232368,"domain_scores_codex":[0.996057,0.002298525,0.0001769213,0.0002287437,0.0006033545,0.0006354257],"domain_scores_gemma":[0.9852315,0.0102898,0.00137793,0.0008567119,0.0006894511,0.00155463],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001467511,0.004804394,0.2709698,0.001673129,0.0001569947,0.2186778,0.1529211,0.01569573,0.009320054,0.03980872,0.02472495,0.2597798],"study_design_scores_gemma":[0.0003445103,0.00506127,0.1457886,0.001275252,0.0004110922,0.1622939,0.3324624,0.07077193,0.02826251,0.02207458,0.2307285,0.0005255071],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9419688,0.0006038718,0.01546258,0.01674513,0.000100589,0.0003440447,0.0003375619,0.0002558544,0.02418152],"genre_scores_gemma":[0.9841744,0.0004305113,0.01067282,0.0005459546,0.00004564351,0.00009913825,0.00007895552,0.00002879595,0.003923794],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006822914,"threshold_uncertainty_score":0.01789701,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06225392313681461,"score_gpt":0.3150384640280711,"score_spread":0.2527845408912565,"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."}}