{"id":"W4313800421","doi":"10.1093/bioadv/vbac099","title":"GlobeCorr: interactive globe-based visualization for correlation datasets","year":2023,"lang":"en","type":"article","venue":"Bioinformatics Advances","topic":"Health, Environment, Cognitive Aging","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Public Health Ontario; University of Toronto; McGill University Health Centre; Simon Fraser University","funders":"Canadian Institutes of Health Research; Genome Canada","keywords":"Metadata; Visualization; Computer science; MIT License; Pairwise comparison; Data mining; Correlation; Interactive visualization; Data visualization; Information retrieval; Globe; License; Data science; World Wide Web; Artificial intelligence; Biology","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000438276,0.0001458524,0.0001252721,0.00007544496,0.000223322,0.00004268316,0.0001586697,0.00005337482,0.0002463036],"category_scores_gemma":[0.0003051904,0.0001415483,0.00004070235,0.0003881616,0.00008777619,0.001356188,0.00009901413,0.0000689154,0.001666117],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002430484,"about_ca_system_score_gemma":0.00001824077,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002089124,"about_ca_topic_score_gemma":0.00005304363,"domain_scores_codex":[0.9987522,0.00003303797,0.0003686532,0.000229593,0.0002994099,0.0003170422],"domain_scores_gemma":[0.9991323,0.0002785465,0.0002575584,0.0002291774,0.00001022668,0.0000922145],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002375427,0.0002471295,0.04913094,0.0005111633,0.00003679261,0.00000622367,0.002954195,0.1935981,0.000941663,0.0009154217,0.02962784,0.721793],"study_design_scores_gemma":[0.0005403103,0.0001022494,0.01293701,0.00004384285,0.00001364893,0.000001137535,0.0005344934,0.7970034,0.0008500154,0.0005554371,0.1872023,0.0002161545],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0445447,0.00004018356,0.9436131,0.0003384078,0.0007619182,0.001833373,0.001025644,0.0003241929,0.007518499],"genre_scores_gemma":[0.921429,0.0004073252,0.0638902,0.003230774,0.0001650606,0.0004535152,0.009966822,0.00007687441,0.0003804593],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8797229,"threshold_uncertainty_score":0.9991112,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01610781482344448,"score_gpt":0.3134939633144855,"score_spread":0.297386148491041,"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."}}