{"id":"W2789898034","doi":"10.21037/aes.2018.ab046","title":"AB046. The retinoblastoma model for translational research","year":2018,"lang":"en","type":"article","venue":"Annals of Eye Science","topic":"Neuroblastoma Research and Treatments","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre Hospitalier Universitaire Sainte-Justine; Hôpital Maisonneuve-Rosemont; Université de Montréal","funders":"","keywords":"Retinoblastoma; Preclinical testing; Pharmacodynamics; Pharmacokinetics; Medicine; Fundus (uterus); Computer science; In vivo; Translational research; Human disease; Pharmacology; Computational biology; Medical physics; Pathology; Biotechnology; Ophthalmology; Biology; Disease","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00179021,0.0006404369,0.00045214,0.001909721,0.001030883,0.0007601184,0.001090013,0.0009309763,0.01331256],"category_scores_gemma":[0.0003910554,0.0003269104,0.0008709025,0.00105816,0.0005379792,0.000838985,0.0008897997,0.001709944,0.006271034],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001136574,"about_ca_system_score_gemma":0.002176222,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0038874,"about_ca_topic_score_gemma":0.006754094,"domain_scores_codex":[0.9988109,0.0002063128,0.0001131832,0.0001422549,0.000580732,0.0001466291],"domain_scores_gemma":[0.9994305,0.00004947935,0.0001094014,0.0001942993,0.00008132946,0.0001349543],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003263754,0.002347972,0.003581811,0.0006643875,0.00008462703,0.002057432,0.0003245076,0.0008810302,0.8943182,0.01222873,0.0158543,0.06439323],"study_design_scores_gemma":[0.0009177256,0.008077103,0.007927168,0.0003403028,0.0002903312,0.01185694,0.0003280591,0.003940125,0.6669237,0.003407484,0.2959148,0.00007624369],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.649955,0.02664188,0.1110875,0.008454259,0.004200823,0.006796188,0.02729531,0.008035932,0.1575331],"genre_scores_gemma":[0.7516501,0.01437525,0.109124,0.001500331,0.0002836232,0.005360235,0.01843256,0.0005870255,0.09868689],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01331256,"threshold_uncertainty_score":0.04453492,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3763959792065565,"score_gpt":0.5465221620593291,"score_spread":0.1701261828527726,"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."}}