{"id":"W4386469584","doi":"10.32920/24093720","title":"Mining significant high utility gene regulation sequential patterns","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University; Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Gene; Microarray; Microarray analysis techniques; Gene expression; Computational biology; Biology; Genetics","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":[0.001109276,0.0008814558,0.000941433,0.00293527,0.000558592,0.001125338,0.001282915,0.0008805014,0.002618244],"category_scores_gemma":[0.004393661,0.0003682802,0.001529012,0.002956001,0.000540096,0.0008982448,0.00103945,0.0007659989,0.0009706277],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006848002,"about_ca_system_score_gemma":0.001153194,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003414192,"about_ca_topic_score_gemma":0.006758424,"domain_scores_codex":[0.9986725,0.0002276468,0.0001153695,0.0004867472,0.0003481646,0.0001497287],"domain_scores_gemma":[0.9982181,0.0008328541,0.0002013638,0.0003656074,0.0002814783,0.0001006239],"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":[0.0009507588,0.0006240395,0.1140999,0.001096542,0.0004139407,0.001638843,0.000341843,0.06496291,0.03245735,0.0186716,0.03018377,0.7345586],"study_design_scores_gemma":[0.0001045308,0.0002173544,0.0394596,0.00008418898,0.0001509613,0.001446657,0.0002258026,0.8706762,0.01447297,0.0560037,0.01711088,0.00004714222],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2864693,0.002909069,0.6812478,0.001855069,0.0001340673,0.0004372003,0.01654275,0.005398621,0.005006037],"genre_scores_gemma":[0.7865481,0.0008661753,0.1834069,0.0004953612,0.0001363832,0.0003603214,0.02260111,0.0002392684,0.005346265],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003414192,"threshold_uncertainty_score":0.008758903,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07948044337412871,"score_gpt":0.2954129372179342,"score_spread":0.2159324938438054,"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."}}