{"id":"W2615328073","doi":"10.1016/j.clinimag.2005.07.003","title":"CT screening for lung cancer","year":2005,"lang":"en","type":"article","venue":"Clinical Imaging","topic":"Lung Cancer Diagnosis and Treatment","field":"Medicine","cited_by":56,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Overdiagnosis; Medicine; Malignancy; Lung cancer; Nodule (geology); Lung cancer screening; Cancer; Radiology; Medical diagnosis; Lung; Stage (stratigraphy); Internal medicine","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":[0.0002272441,0.0002757375,0.0002458765,0.001705123,0.0004471114,0.0005143924,0.0002818269,0.000616049,0.01512843],"category_scores_gemma":[0.002151065,0.0001684461,0.0003482075,0.001021298,0.0003023104,0.0003945406,0.0002398249,0.0005737356,0.002200063],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005520189,"about_ca_system_score_gemma":0.0008718719,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003971472,"about_ca_topic_score_gemma":0.005691553,"domain_scores_codex":[0.9998216,0.00004089402,0.00001825003,0.00002607981,0.00005746794,0.00003575743],"domain_scores_gemma":[0.9994592,0.0001839419,0.00006820634,0.00004584348,0.0001259176,0.0001168722],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008591638,0.0003862054,0.5704997,0.0006263611,0.0001844451,0.02014061,0.0001854301,0.0005954581,0.01496045,0.002642961,0.05552103,0.3333982],"study_design_scores_gemma":[0.0000917944,0.0007844506,0.7168502,0.0007267926,0.0003601214,0.1414081,0.0002416172,0.001107766,0.007989413,0.002657838,0.1277407,0.00004121355],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.4000981,0.08604456,0.005514215,0.01658355,0.001062509,0.0003590936,0.003296152,0.0003731761,0.4866687],"genre_scores_gemma":[0.9264434,0.02835856,0.004426835,0.004267225,0.001705772,0.00007470993,0.001741805,0.00007351589,0.03290816],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01512843,"threshold_uncertainty_score":0.05060965,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07114450813215384,"score_gpt":0.4808042470686708,"score_spread":0.409659738936517,"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."}}