{"id":"W4394115072","doi":"10.6084/m9.figshare.23658339","title":"Additional file 1 of Dynamic profiling of medulloblastoma surfaceome","year":2023,"lang":"en","type":"dataset","venue":"Figshare","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University Health Network; University of Toronto; McMaster University","funders":"","keywords":"Profiling (computer programming); Medulloblastoma; Computer science; Computational biology; Biology; Operating system; Cancer research","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001027119,0.00144106,0.001408116,0.001650135,0.0008582412,0.001790295,0.001658397,0.001201492,0.7478322],"category_scores_gemma":[0.008696944,0.0005621953,0.0007504005,0.002236399,0.0002278522,0.001204957,0.001181727,0.0009581115,0.1693572],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009292407,"about_ca_system_score_gemma":0.00175982,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005440591,"about_ca_topic_score_gemma":0.01258073,"domain_scores_codex":[0.9994422,0.00007195574,0.00005926424,0.0001755551,0.0001648109,0.00008638461],"domain_scores_gemma":[0.9966964,0.0022019,0.0001779465,0.000319927,0.0004226361,0.0001812352],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004136938,0.00009266072,0.001932555,0.003385287,0.00007509148,0.0001344653,0.00005618313,0.0008265174,0.001316156,0.0008008907,0.9789837,0.01198293],"study_design_scores_gemma":[0.002123237,0.0002870459,0.01921462,0.001572578,0.0001869599,0.0005904495,0.0002252227,0.003638565,0.004181466,0.007873176,0.9599728,0.0001338708],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002111008,0.00003873642,0.0004015884,0.00005250411,0.00002097257,0.00003730937,0.9980204,0.000603078,0.0006143575],"genre_scores_gemma":[0.004097091,0.0001320229,0.003391089,0.0002976811,0.00003677685,0.0006499953,0.9869452,0.001043522,0.003406688],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7478322,"threshold_uncertainty_score":0.3596867,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01564397966786069,"score_gpt":0.2904523343145937,"score_spread":0.274808354646733,"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."}}