{"id":"W4234912275","doi":"10.1136/jitc-2020-001472","title":"Society for Immunotherapy of Cancer clinical and biomarkers data sharing resource document: Volume II—practical challenges","year":2020,"lang":"en","type":"article","venue":"Journal for ImmunoTherapy of Cancer","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Jewish General Hospital","funders":"National Cancer Institute; Society for Immunotherapy of Cancer","keywords":"Data sharing; Clinical trial; Medicine; Resource (disambiguation); Biomarker; Data science; Biomarker discovery; Data collection; Computer science; Medical physics; Alternative medicine; Pathology","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":["metaresearch","open_science"],"consensus_categories":[],"category_scores_codex":[0.1772964,0.001005797,0.002205099,0.004345185,0.004226252,0.01691023,0.008883758,0.009215546,0.0387627],"category_scores_gemma":[0.1499285,0.001641668,0.002620095,0.00501196,0.003334661,0.009691052,0.01337876,0.01272136,0.04095673],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0073574,"about_ca_system_score_gemma":0.08468863,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006887257,"about_ca_topic_score_gemma":0.006020417,"domain_scores_codex":[0.8826537,0.04882549,0.01501269,0.004970275,0.04262189,0.005916076],"domain_scores_gemma":[0.6723077,0.06827155,0.01839058,0.0700688,0.1334068,0.03755457],"domain_codex":null,"domain_gemma":"reproducibility","domain_candidate":"reproducibility","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001169823,0.0001464766,0.00120021,0.0003281091,0.00003685162,0.0000691188,0.0001666597,0.0004743924,0.0008039618,0.01225376,0.8899271,0.09447644],"study_design_scores_gemma":[0.00006576416,0.0001269919,0.001245254,0.0005787401,0.00001619017,0.0001333971,0.0001729642,0.0007256673,0.0005152909,0.005810722,0.9905681,0.00004093261],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"methods","genre_scores_codex":[0.004132591,0.005566909,0.08184911,0.6573093,0.05614223,0.01361481,0.01822697,0.00520025,0.1579578],"genre_scores_gemma":[0.04121534,0.01190002,0.2416065,0.3093655,0.04198343,0.02577473,0.08028001,0.004567188,0.2433072],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9911162,"threshold_uncertainty_score":0.937644,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08466978870647565,"score_gpt":0.4076963484725098,"score_spread":0.3230265597660341,"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."}}