{"id":"W4240675212","doi":"10.1055/s-0040-1702030","title":"Welcome to IMIA","year":2020,"lang":"en","type":"article","venue":"Yearbook of Medical Informatics","topic":"Healthcare Systems and Reforms","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Officer; Library science; Political science; Management; Geography; Law","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005594293,0.0000725203,0.0003281436,0.00007329121,0.00002147228,0.00001339854,0.0002961706,0.0001438311,0.0007181114],"category_scores_gemma":[0.0002595895,0.0000597384,0.00006248678,0.0001634521,0.00003432135,0.00009004428,0.00009670034,0.0001759305,0.002431654],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002519691,"about_ca_system_score_gemma":0.00005560108,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002013192,"about_ca_topic_score_gemma":0.000004360698,"domain_scores_codex":[0.998596,0.000004089201,0.0009860346,0.00006836439,0.0001583208,0.0001871776],"domain_scores_gemma":[0.9991167,0.00001068833,0.0002011178,0.0001507387,0.00002079609,0.0004999911],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005613271,0.0001575369,0.01887269,0.004087111,0.000215736,0.00002633877,0.06274866,0.0001346639,0.00001372297,0.7155643,0.09150954,0.1066135],"study_design_scores_gemma":[0.0007371713,0.000340973,0.0033829,0.0001583727,0.000001356068,0.000006639269,0.001169732,0.01394626,0.00008069288,0.001915123,0.9779792,0.0002815484],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4704135,0.001101128,0.06066853,0.08364329,0.003146897,0.001264054,0.0002336793,0.0002280448,0.3793009],"genre_scores_gemma":[0.9827064,0.0001358741,0.003139489,0.01284679,0.0006904824,0.00001148211,0.000007410077,0.00001942767,0.0004426065],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8864697,"threshold_uncertainty_score":0.9983451,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06043450636610531,"score_gpt":0.2704869193681937,"score_spread":0.2100524130020884,"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."}}