{"id":"W6921486993","doi":"10.6084/m9.figshare.c.6735546","title":"Dynamic profiling of medulloblastoma surfaceome","year":2023,"lang":"en","type":"other","venue":"Figshare","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University Health Network; University of Toronto; McMaster University","funders":"","keywords":"Medulloblastoma; Neurocognitive; Suppressor; Gene knockdown; Profiling (computer programming); Clinical trial","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":[0.00009322955,0.0002551733,0.0001597274,0.0003994404,0.0001616444,0.0003651924,0.0001349098,0.0001927903,0.002870644],"category_scores_gemma":[0.0001346651,0.00008416979,0.0002056381,0.0003270703,0.00008609781,0.0001974608,0.0002522514,0.0003462374,0.001125971],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003211284,"about_ca_system_score_gemma":0.0001391178,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001021775,"about_ca_topic_score_gemma":0.001560881,"domain_scores_codex":[0.999909,0.000005909093,0.000003576262,0.00002393493,0.00003569946,0.00002193456],"domain_scores_gemma":[0.9999626,0.000005523525,0.000008665179,0.000005576677,0.00001024707,0.000007381072],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0001224301,0.00002023618,0.001582854,0.00005329231,0.00001140995,0.00005121945,0.00002037056,0.00041978,0.9865675,0.0002063878,0.001105989,0.009838567],"study_design_scores_gemma":[0.00001531756,0.00024854,0.04468524,0.00001770532,0.00003574012,0.0005113658,0.00009082563,0.009360438,0.9143035,0.0003787832,0.03032899,0.00002351592],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9552225,0.001728869,0.01911283,0.0003608265,0.00008221254,0.00008722766,0.01256887,0.0007421425,0.01009446],"genre_scores_gemma":[0.9590812,0.001575129,0.01487953,0.0001744686,0.00001610225,0.00009816958,0.01481515,0.0001749581,0.009185191],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002870644,"threshold_uncertainty_score":0.009603262,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03479297307961481,"score_gpt":0.2973529414053417,"score_spread":0.2625599683257269,"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."}}