{"id":"W4394078566","doi":"10.6084/m9.figshare.23962118","title":"Additional file 8 of BamQuery: a proteogenomic tool to explore the immunopeptidome and prioritize actionable tumor antigens","year":2023,"lang":"en","type":"dataset","venue":"Figshare","topic":"Monoclonal and Polyclonal Antibodies Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute for Research in Immunology and Cancer; Université de Montréal","funders":"","keywords":"Computer science; Computational biology; Information retrieval; Biology","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":[0.001703292,0.00264526,0.002309172,0.003799504,0.001082751,0.002853354,0.003442296,0.002351721,0.3911417],"category_scores_gemma":[0.010369,0.0009778067,0.001700872,0.005228182,0.0004346494,0.00165328,0.00193947,0.001757312,0.160827],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001645319,"about_ca_system_score_gemma":0.002548353,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01180011,"about_ca_topic_score_gemma":0.02184867,"domain_scores_codex":[0.9989303,0.0001498294,0.0001455071,0.0003816414,0.0002046494,0.0001879819],"domain_scores_gemma":[0.9954134,0.002558613,0.0003438529,0.0006268378,0.0007475363,0.0003097784],"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":[0.0002502511,0.00005405984,0.001810433,0.003173039,0.00008669555,0.00005559151,0.00004614085,0.0004059326,0.0005570484,0.0004833609,0.9895074,0.003570103],"study_design_scores_gemma":[0.001414459,0.00009026848,0.009636282,0.0009734932,0.0001795517,0.0002379805,0.0001687419,0.001043917,0.002045903,0.004102397,0.980018,0.00008917174],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005182869,0.0000206979,0.00007193965,0.00002581641,0.000007901397,0.0000119049,0.9992445,0.000348518,0.0002170379],"genre_scores_gemma":[0.0004979189,0.00004126895,0.000559758,0.00005750718,0.000006341782,0.0001494393,0.9979542,0.0002039073,0.0005296994],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3911417,"threshold_uncertainty_score":0.8684624,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06815076625749775,"score_gpt":0.3151851817127592,"score_spread":0.2470344154552614,"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."}}