{"id":"W4281720443","doi":"10.1016/j.jtocrr.2022.100350","title":"Expected Cost Savings From Low-Dose Computed Tomography Scan Screening for Lung Cancer in Alberta, Canada","year":2022,"lang":"en","type":"article","venue":"JTO Clinical and Research Reports","topic":"Lung Cancer Diagnosis and Treatment","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Impact; Alberta Health Services; University of Alberta; University of Calgary; Alberta Health","funders":"","keywords":"Medicine; Medical prescription; Lung cancer screening; Stage (stratigraphy); Lung cancer; Computed tomography; Health care; Cost–benefit analysis; Emergency medicine; Intensive care medicine; Radiology; Internal medicine","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":[],"consensus_categories":[],"category_scores_codex":[0.001066378,0.0004813092,0.0002921394,0.001013985,0.000664101,0.001526248,0.001092881,0.0005693278,0.003362237],"category_scores_gemma":[0.003112634,0.0002470503,0.0007211709,0.001611337,0.0004263103,0.0003119111,0.0004742802,0.000561582,0.0002067047],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05351052,"about_ca_system_score_gemma":0.04405567,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9746177,"about_ca_topic_score_gemma":0.9719902,"domain_scores_codex":[0.9988564,0.0002703592,0.00004262176,0.00006993326,0.0003413242,0.000419302],"domain_scores_gemma":[0.9986174,0.0003531951,0.0001670675,0.0000219504,0.0005336215,0.000306724],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001474929,0.0003328596,0.6060585,0.000422016,0.0005879003,0.001105023,0.0002466333,0.3150859,0.001612223,0.01024176,0.01145549,0.0513768],"study_design_scores_gemma":[0.000618276,0.0007392769,0.5293491,0.0003357054,0.0008495447,0.0008747668,0.001594599,0.4446926,0.001547017,0.004872527,0.01439294,0.0001336276],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9563052,0.002061604,0.003555245,0.005112627,0.00007856185,0.0002777853,0.01260408,0.0001371379,0.01986778],"genre_scores_gemma":[0.9919008,0.0007154275,0.00155597,0.0002493837,0.00001283056,0.00002514218,0.002244456,0.000007361938,0.003288582],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05351052,"threshold_uncertainty_score":0.3882478,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06801608925398014,"score_gpt":0.4345918053243477,"score_spread":0.3665757160703675,"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."}}