{"id":"W2065598197","doi":"10.1177/0272989x0002000208","title":"Perception of Quantitative Information for Treatment Decisions","year":2000,"lang":"en","type":"article","venue":"Medical Decision Making","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":186,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Context (archaeology); Task (project management); Computer science; Perception; Statistics; Artificial intelligence; Mathematics; Psychology; Engineering","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":[0.01103727,0.0006648302,0.000485503,0.001282685,0.0002522914,0.002455421,0.0003817211,0.0007187181,0.007730303],"category_scores_gemma":[0.1362561,0.0002633365,0.0005761093,0.0006353087,0.0005270545,0.002837962,0.0008688081,0.0008081279,0.000674717],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006331269,"about_ca_system_score_gemma":0.0003894395,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003602497,"about_ca_topic_score_gemma":0.0001886121,"domain_scores_codex":[0.991541,0.00584653,0.0005016411,0.000386937,0.001524042,0.0001999112],"domain_scores_gemma":[0.861049,0.1193416,0.01030684,0.003235555,0.004540426,0.001526665],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.01672792,0.001411866,0.1359594,0.002625476,0.0003854417,0.0006696775,0.01354742,0.01147301,0.05608593,0.007706342,0.005764748,0.7476428],"study_design_scores_gemma":[0.002387777,0.03791776,0.6073847,0.002911028,0.00167716,0.007166096,0.02744439,0.1333147,0.07982055,0.04604042,0.05244167,0.001493827],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9381323,0.001629724,0.04968214,0.001295988,0.0001649582,0.0003860265,0.0005243905,0.0004219224,0.007762535],"genre_scores_gemma":[0.9819163,0.0003120178,0.01698819,0.0001400336,0.00006316685,0.00008762609,0.0001197516,0.00004066722,0.0003321428],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01103727,"threshold_uncertainty_score":0.05837137,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05602459499976107,"score_gpt":0.4035731194010411,"score_spread":0.34754852440128,"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."}}