{"id":"W2470329500","doi":"10.1002/cyto.b.21393","title":"Use FlowRepository to share your clinical data upon study publication","year":2016,"lang":"en","type":"article","venue":"Cytometry Part B Clinical Cytometry","topic":"Single-cell and spatial transcriptomics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; BC Cancer Agency","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Data sharing; Computer science; Publishing; Data publishing; Data science; Open data; Data quality; World Wide Web; Medicine; Political science; Business; Pathology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.004205402,0.0004756695,0.0008375338,0.0004112517,0.0002107471,0.0002476708,0.002114862,0.0007559467,0.0002129635],"category_scores_gemma":[0.01299462,0.0003657633,0.0004106647,0.001216532,0.0002055399,0.00008870041,0.001387831,0.0004999147,0.0006879737],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005130547,"about_ca_system_score_gemma":0.000236284,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002022218,"about_ca_topic_score_gemma":0.00004693782,"domain_scores_codex":[0.9933141,0.0008368025,0.002213431,0.002253864,0.0006536221,0.0007281522],"domain_scores_gemma":[0.9933318,0.0008174456,0.0003940839,0.003961565,0.0005664807,0.0009286624],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006854303,0.002546506,0.8840105,0.00001639364,0.0003330631,0.00002191891,0.00001306956,8.761363e-7,0.02774536,0.000005690799,0.05104487,0.03357633],"study_design_scores_gemma":[0.003606836,0.003388266,0.6190892,0.00008317983,0.0001984377,0.0000189866,0.00008507344,0.00005313497,0.006451468,0.000008006852,0.366076,0.0009414341],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9863,0.0002066982,0.007563207,0.0007585394,0.003181195,0.0009104161,0.000624944,0.000134054,0.0003209315],"genre_scores_gemma":[0.988899,0.0002720394,0.001541944,0.00201743,0.003912608,0.00005241265,0.0007261867,0.0001046815,0.002473727],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3150311,"threshold_uncertainty_score":0.9998794,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2957658866390204,"score_gpt":0.4364505748038122,"score_spread":0.1406846881647918,"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."}}