{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005472468,0.002799404,0.001812356,0.004678364,0.001365235,0.004516028,0.003754147,0.001692707,0.1145419],"category_scores_gemma":[0.01919118,0.001122407,0.002464475,0.005572009,0.0009900447,0.005013171,0.006493488,0.003122001,0.02835698],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000956304,"about_ca_system_score_gemma":0.002334228,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006317288,"about_ca_topic_score_gemma":0.008010342,"domain_scores_codex":[0.9978216,0.0005539375,0.0002043596,0.0004765563,0.0007549675,0.0001886582],"domain_scores_gemma":[0.9890627,0.006060927,0.0006064535,0.001899313,0.001713135,0.0006573909],"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":[0.0006816417,0.0001057655,0.002721945,0.001132632,0.0002330474,0.0004415088,0.000754515,0.003106934,0.004912824,0.007380893,0.8986785,0.07984977],"study_design_scores_gemma":[0.001103288,0.0002240521,0.01317596,0.001143067,0.0002985543,0.001228489,0.0006833755,0.13612,0.03067488,0.08082433,0.7338703,0.0006537561],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"software","genre_gemma":"software","genre_scores_codex":[0.004612208,0.0004799424,0.2248041,0.00165875,0.0005169341,0.0003819735,0.07721884,0.6786938,0.01163347],"genre_scores_gemma":[0.07582825,0.001307336,0.6047326,0.001880118,0.0004910808,0.002381287,0.1510879,0.1502204,0.01207092],"genre_candidate":"software","genre_consensus":"software","teacher_disagreement_score":0.1145419,"threshold_uncertainty_score":0.3831808,"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."}}