{"id":"W4200433420","doi":"10.3390/onco1020016","title":"Open Data to Support CANCER Science—A Bioinformatics Perspective on Glioma Research","year":2021,"lang":"en","type":"article","venue":"Onco","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Data science; Medical research; Perspective (graphical); Cancer; Glioma; Open research; Bioinformatics; Artificial intelligence; Medicine; World Wide Web; Biology; 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":["open_science"],"consensus_categories":[],"category_scores_codex":[0.03287183,0.0007578448,0.001539232,0.00827481,0.001923973,0.01174541,0.004720853,0.003364783,0.009461898],"category_scores_gemma":[0.08814047,0.000623662,0.001519503,0.0174877,0.004492761,0.01584613,0.01123881,0.006517912,0.003125429],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00254113,"about_ca_system_score_gemma":0.007274886,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003580857,"about_ca_topic_score_gemma":0.003209426,"domain_scores_codex":[0.9839553,0.009881322,0.001423755,0.001434144,0.002791837,0.0005135298],"domain_scores_gemma":[0.8724176,0.08212934,0.005225339,0.02619201,0.007590323,0.006445379],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004228955,0.0001764883,0.00497686,0.002510809,0.0002269066,0.0006147023,0.001716897,0.008016175,0.002349935,0.6225792,0.09171309,0.2646962],"study_design_scores_gemma":[0.00004927027,0.00004402647,0.001216012,0.001189449,0.0000466417,0.0002897241,0.001061439,0.007993271,0.001950965,0.5679119,0.4181673,0.00007988472],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01058422,0.02632913,0.6449509,0.2288132,0.003520533,0.0004747577,0.0348746,0.009313785,0.04113895],"genre_scores_gemma":[0.1581834,0.03138306,0.7299913,0.01438911,0.003377736,0.0009870098,0.05246387,0.003197113,0.006027383],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9952791,"threshold_uncertainty_score":0.1738449,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1388589533307628,"score_gpt":0.4551647386507778,"score_spread":0.316305785320015,"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."}}