{"id":"W2018120078","doi":"10.1155/2009/535869","title":"Transition Dependency: A Gene-Gene Interaction Measure for Times Series Microarray Data","year":2009,"lang":"en","type":"article","venue":"EURASIP Journal on Bioinformatics and Systems Biology","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Dependency (UML); Computer science; Pairwise comparison; Data mining; Gene interaction; Measure (data warehouse); Bivariate analysis; Markov chain; Machine learning; Artificial intelligence; Gene; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000866798,0.0002550879,0.0003155951,0.0001083714,0.0002848641,0.0001860604,0.0003359584,0.0003019622,0.000004255062],"category_scores_gemma":[0.00005253773,0.0001971586,0.00009781316,0.000056578,0.00005688415,0.0000547463,0.00004918904,0.0002221486,0.000007380037],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002164876,"about_ca_system_score_gemma":0.00007816932,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002593764,"about_ca_topic_score_gemma":0.000005504252,"domain_scores_codex":[0.9985024,0.00007539501,0.0007519722,0.0002203371,0.0001090313,0.0003408577],"domain_scores_gemma":[0.998824,0.00002493441,0.0004197335,0.0004209941,0.0001612441,0.000149067],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.004908522,0.0004387159,0.0003389682,0.0005651158,0.001537247,0.00002310143,0.003301135,0.002748301,0.6598726,0.009604244,0.06052152,0.2561405],"study_design_scores_gemma":[0.014475,0.02634372,0.001233252,0.0009980149,0.0006579983,0.02662829,0.006420503,0.2162554,0.06643768,0.0116999,0.6243777,0.004472493],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3411897,0.0101796,0.6309661,0.004182966,0.005325795,0.002334554,0.001655529,0.00007900283,0.004086782],"genre_scores_gemma":[0.9874855,0.001256361,0.007691303,0.0009185164,0.001045805,0.000009525646,0.0013981,0.00002003154,0.0001748025],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6462959,"threshold_uncertainty_score":0.8039894,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02600205943012991,"score_gpt":0.268564878119404,"score_spread":0.2425628186892741,"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."}}