{"id":"W4303491825","doi":"10.1101/2022.10.07.511250","title":"BioDiscViz : a visualization support and consensus signature selector for BioDiscML results","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Gene expression and cancer classification","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Overfitting; Computer science; Bootstrapping (finance); Visualization; Machine learning; Flexibility (engineering); Field (mathematics); Artificial intelligence; Data mining; Data science; Artificial neural network; Statistics","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":[],"consensus_categories":[],"category_scores_codex":[0.006043453,0.003751304,0.001856097,0.006546462,0.0009810484,0.004620211,0.003681572,0.001869532,0.06970318],"category_scores_gemma":[0.01794306,0.001215427,0.002399907,0.002573299,0.0009046014,0.003620331,0.00451662,0.002425298,0.01801619],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001620119,"about_ca_system_score_gemma":0.001768092,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003634187,"about_ca_topic_score_gemma":0.003314771,"domain_scores_codex":[0.9979283,0.0004366938,0.000233924,0.0003796472,0.0008154399,0.0002060206],"domain_scores_gemma":[0.9917779,0.004814407,0.0006074697,0.001014417,0.001420432,0.0003654716],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003083362,0.0004586912,0.007059698,0.00249417,0.0003819271,0.001532758,0.001282958,0.01807068,0.02330347,0.02550627,0.6595894,0.2572365],"study_design_scores_gemma":[0.001304072,0.000281437,0.005398862,0.001051491,0.0001787865,0.001174009,0.0004891614,0.4467805,0.1153181,0.06357822,0.3638673,0.0005780911],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"software","genre_gemma":"methods","genre_scores_codex":[0.005571179,0.0002492348,0.3479064,0.0007992223,0.0002427409,0.0002184664,0.02529081,0.6150585,0.004663505],"genre_scores_gemma":[0.1060254,0.0007527597,0.6236306,0.001565038,0.000256492,0.002067968,0.07874568,0.1749142,0.01204187],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.06970318,"threshold_uncertainty_score":0.2331804,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01494716149718914,"score_gpt":0.2574474547830518,"score_spread":0.2425002932858626,"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."}}