{"id":"W2004457097","doi":"10.2165/11532250-000000000-00000","title":"Measuring Preferences for Colorectal Cancer Screening","year":2010,"lang":"en","type":"article","venue":"Patient","topic":"Colorectal Cancer Screening and Detection","field":"Medicine","cited_by":42,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary; Alberta Health Services","funders":"American College of Gastroenterology; American Society for Gastrointestinal Endoscopy","keywords":"Conjoint analysis; Context (archaeology); Population; Test (biology); Preference; Sample (material); MEDLINE; Medicine; Health care; Descriptive statistics; Family medicine; Psychology; Computer science; Statistics; Environmental health","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":[0.003584345,0.0002653381,0.0004059389,0.0009647148,0.0006079615,0.0009186408,0.0002925913,0.000814033,0.006852459],"category_scores_gemma":[0.01726305,0.0001620058,0.001033761,0.0009036899,0.0003726165,0.0007772923,0.0006761582,0.0009667538,0.0006701762],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007498072,"about_ca_system_score_gemma":0.0006271032,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001383073,"about_ca_topic_score_gemma":0.002924815,"domain_scores_codex":[0.9973353,0.001280431,0.0003878066,0.0001648878,0.0005489215,0.0002826032],"domain_scores_gemma":[0.9878926,0.006415132,0.00296878,0.0003239388,0.0007283216,0.001671336],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001238803,0.0006876605,0.9759335,0.00007507421,0.0002865455,0.00008774998,0.0004854536,0.0002956119,0.000391883,0.0002008586,0.0009162145,0.0194006],"study_design_scores_gemma":[0.0001328126,0.003292295,0.9890997,0.00004918891,0.0002109914,0.0009553483,0.001512193,0.001514427,0.0006764624,0.0004736437,0.002041193,0.00004176436],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9942551,0.0002053095,0.0002071127,0.0003096051,0.00001597343,0.00004966713,0.0003703628,0.000007543905,0.004579294],"genre_scores_gemma":[0.9982297,0.0001228729,0.0007080313,0.0001805792,0.00001739557,0.00003939497,0.0002329362,0.000002916104,0.0004662317],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006852459,"threshold_uncertainty_score":0.02292371,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05516739436294571,"score_gpt":0.2876969328513791,"score_spread":0.2325295384884334,"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."}}