{"id":"W2995016195","doi":"10.1038/s42256-019-0133-1","title":"Publisher Correction: Intelligent feature engineering and ontological mapping of brain tumour histomorphologies by deep learning","year":2019,"lang":"en","type":"article","venue":"Nature Machine Intelligence","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University Health Network; Princess Margaret Cancer Centre; University of Toronto","funders":"","keywords":"Feature (linguistics); Computer science; Feature engineering; Artificial intelligence; Deep learning; Philosophy; Linguistics","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":"codex-gemma-dda1882f352a","candidate_categories":["research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0006233706,0.0002941133,0.0005632906,0.0002313879,0.00006919634,0.00005554724,0.0002356332,0.0004414657,0.0002351301],"category_scores_gemma":[0.003142198,0.0002350265,0.000125408,0.0003934376,0.0001382025,0.0001263123,0.0001468672,0.003517491,0.0000142687],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001055056,"about_ca_system_score_gemma":0.00003279245,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007811144,"about_ca_topic_score_gemma":0.000003830664,"domain_scores_codex":[0.9982696,0.00007650647,0.0003870402,0.0005088612,0.0003950596,0.0003629157],"domain_scores_gemma":[0.9987046,0.0005400614,0.0001833428,0.0002430481,0.0001421288,0.000186882],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005094616,0.0004101247,0.297504,0.001130931,0.0003894843,0.0002970622,0.002074481,0.007714766,0.08535393,0.002802928,0.1003305,0.5014823],"study_design_scores_gemma":[0.001103039,0.001356828,0.04432546,0.00116597,0.0001425846,0.002698463,0.001418345,0.6036455,0.0119183,0.0003668191,0.330745,0.00111367],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6376314,0.05785386,0.2536405,0.02704719,0.009842518,0.001445081,0.000006372689,0.000841221,0.01169195],"genre_scores_gemma":[0.9869564,0.0003681383,0.004968877,0.001118261,0.0001097771,0.000007911524,0.00005118337,0.00003742524,0.00638198],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5959307,"threshold_uncertainty_score":0.9987814,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005744666744943967,"score_gpt":0.2530969551124466,"score_spread":0.2473522883675026,"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."}}