{"id":"W4402260278","doi":"10.1038/s41698-024-00695-7","title":"A multimodal neural network with gradient blending improves predictions of survival and metastasis in sarcoma","year":2024,"lang":"en","type":"article","venue":"npj Precision Oncology","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; University of Toronto; McGill University Health Centre","funders":"National Cancer Institute; Fondation du cancer des Cèdres; Strong","keywords":"Artificial neural network; Sarcoma; Metastasis; Multimodal therapy; Computer science; Artificial intelligence; Medicine; Internal medicine; Cancer; Pathology","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.0007621202,0.0001235357,0.0004289656,0.0002283684,0.00005069201,0.00001696103,0.000064406,0.00008905927,0.00004101827],"category_scores_gemma":[0.0002415433,0.0000867268,0.00005605949,0.0003325215,0.0001694907,0.00006740372,0.00007624523,0.0005279123,0.000001477982],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009114988,"about_ca_system_score_gemma":0.0001176103,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001282809,"about_ca_topic_score_gemma":0.00006942693,"domain_scores_codex":[0.99874,0.0001465624,0.0003353997,0.0003100215,0.0002077641,0.0002602584],"domain_scores_gemma":[0.9989015,0.0007218223,0.00006011914,0.0001430819,0.00003702712,0.0001364002],"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":[0.0008990985,0.0003180443,0.06049168,0.0002210927,0.0002219684,0.0005524615,0.00135648,0.005230505,0.005734073,0.001784259,0.001042084,0.9221482],"study_design_scores_gemma":[0.003307776,0.002824762,0.1620379,0.0006263957,0.0002321931,0.0007875254,0.0004361795,0.8074505,0.0001199382,0.0005993767,0.02141038,0.0001670623],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9868197,0.001751813,0.005902864,0.00254999,0.0007892482,0.0003301762,0.000005468052,0.00006278037,0.001787952],"genre_scores_gemma":[0.9878628,0.0002294009,0.01146238,0.00008658808,0.0001869254,0.00002221919,0.00000956608,0.00002133516,0.0001187566],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9219812,"threshold_uncertainty_score":0.3536617,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01680357438550552,"score_gpt":0.3281118091944795,"score_spread":0.311308234808974,"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."}}