{"id":"W3156150685","doi":"10.2196/23161","title":"Data Integration to Improve Real-world Health Outcomes Research for Non–Small Cell Lung Cancer in the United States: Descriptive and Qualitative Exploration","year":2021,"lang":"en","type":"article","venue":"JMIR Cancer","topic":"Lung Cancer Treatments and Mutations","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Eli Lilly and Company","keywords":"Medicine; Cohort; Descriptive statistics; Atezolizumab; Medical record; Nivolumab; Cancer; Internal medicine; Database; Statistics; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.1835069,0.0004307962,0.0005620439,0.006018872,0.004628097,0.006085099,0.001689763,0.0009145745,0.0009797595],"category_scores_gemma":[0.1993484,0.0005208694,0.0008110726,0.007374431,0.007055743,0.008181357,0.008730689,0.002131629,0.00007648042],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01575772,"about_ca_system_score_gemma":0.0242469,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007367855,"about_ca_topic_score_gemma":0.01107432,"domain_scores_codex":[0.8876796,0.09532239,0.004847241,0.002065132,0.00825615,0.001829397],"domain_scores_gemma":[0.7287115,0.2255899,0.01326004,0.00730283,0.02244101,0.002694758],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001426978,0.0002191041,0.07849914,0.003819685,0.0001668976,0.000449253,0.7451486,0.0008570944,0.001560165,0.05274391,0.006436931,0.1099565],"study_design_scores_gemma":[0.00003388527,0.0001581024,0.02067574,0.004302421,0.00008612697,0.0002534041,0.9029337,0.002347731,0.001407645,0.01967685,0.04803679,0.00008755639],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7767344,0.00712056,0.1058844,0.07581055,0.0004721516,0.008380777,0.003649973,0.0001430873,0.02180422],"genre_scores_gemma":[0.9262995,0.002121379,0.06225986,0.003429817,0.00006076047,0.004380148,0.0007381515,0.00004578994,0.0006646437],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1835069,"threshold_uncertainty_score":0.970489,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2393260491004993,"score_gpt":0.5582879789472005,"score_spread":0.3189619298467011,"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."}}