{"id":"W4282914414","doi":"10.2196/30426","title":"Identifying Cases of Shoulder Injury Related to Vaccine Administration (SIRVA) in the United States: Development and Validation of a Natural Language Processing Method","year":2022,"lang":"en","type":"article","venue":"JMIR Public Health and Surveillance","topic":"Intramuscular injections and effects","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medicine; Cohort; Pathology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002092759,0.00006762367,0.0001889305,0.0002667672,0.0001470804,0.00001956595,0.00003457679,0.00002441949,0.000006777381],"category_scores_gemma":[0.0002088668,0.0000515947,0.00001293,0.0008287248,0.00001081893,0.00005641184,0.000025995,0.0001689797,5.74678e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005840178,"about_ca_system_score_gemma":0.0003443014,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001889316,"about_ca_topic_score_gemma":0.0001060611,"domain_scores_codex":[0.9987707,0.0003982992,0.0003353933,0.0001378594,0.0002021144,0.0001556731],"domain_scores_gemma":[0.999496,0.0001250615,0.0001276287,0.00008920236,0.00008674779,0.00007539501],"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":[0.001377081,0.0008054635,0.2714429,0.005548359,0.0001005338,0.0000848773,0.1802753,0.0002169175,0.002337133,0.0003825392,0.0009670252,0.5364618],"study_design_scores_gemma":[0.004293774,0.004004236,0.8424006,0.0003373105,0.00001004419,0.001159561,0.1017059,0.0213521,0.001547497,0.0000398447,0.0226756,0.0004735146],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9953394,0.0007195103,0.0005349302,0.00276807,0.00003599197,0.0005661229,0.000007079698,0.00001290647,0.00001601753],"genre_scores_gemma":[0.9977504,0.00002121142,0.001194641,0.0006858513,0.000007570879,0.00007959553,0.0002317132,0.000006180691,0.00002284249],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5709577,"threshold_uncertainty_score":0.2103971,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03559273168171421,"score_gpt":0.3905044300957257,"score_spread":0.3549116984140114,"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."}}