{"id":"W3202285089","doi":"10.1093/rheumatology/keab735","title":"Association between autoantibodies in systemic sclerosis and cancer in a national registry","year":2021,"lang":"en","type":"article","venue":"Lara D. Veeken","topic":"Systemic Sclerosis and Related Diseases","field":"Medicine","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Jewish General Hospital; University of Calgary; Université de Montréal","funders":"Canadian Institutes of Health Research","keywords":"Medicine; Autoantibody; Internal medicine; Cancer; Odds ratio; Oncology; Cohort; Cancer registry; Fibrillarin; Breast cancer; Immunology; Antibody","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0009254717,0.0001227674,0.0002801664,0.0009535685,0.0004765615,0.000461478,0.0004162688,0.0002547182,0.001652942],"category_scores_gemma":[0.003142303,0.0001573563,0.0002892588,0.002439641,0.0002324347,0.0002467344,0.0004750335,0.0003728598,0.0001497318],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008818409,"about_ca_system_score_gemma":0.00167287,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.134695,"about_ca_topic_score_gemma":0.1770712,"domain_scores_codex":[0.9990397,0.0001975372,0.0001040739,0.0002074497,0.0002963036,0.0001549329],"domain_scores_gemma":[0.9960775,0.0005409897,0.00201133,0.0002891471,0.0006770042,0.0004040687],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001982062,0.000004162087,0.9993442,0.000005300119,0.00001768849,0.00003249718,0.00001676867,0.00001899175,0.00004729507,0.000006687434,0.0001165126,0.0003700374],"study_design_scores_gemma":[0.000003185399,0.000011661,0.9994011,0.00000757224,0.0000157637,0.0001912507,0.00004616089,0.00009342113,0.00002481289,0.000005239738,0.0001981675,0.000001798349],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9966577,0.0004353541,0.00006873268,0.00008561993,0.000006092779,0.000009727407,0.002044564,0.000009781063,0.0006824888],"genre_scores_gemma":[0.9978586,0.0002426564,0.0000861072,0.00002658519,0.000007565342,0.00001131448,0.001661366,0.000001733511,0.0001040542],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.134695,"threshold_uncertainty_score":0.267822,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03104594976923455,"score_gpt":0.285651180837762,"score_spread":0.2546052310685274,"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."}}