{"id":"W3146488696","doi":"10.1109/visual.2002.1183781","title":"GeneVis: visualization tools for genetic regulatory network dynamics","year":2003,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Visualization; Computer science; Focus (optics); Process (computing); Data visualization; Genetic network; Information visualization; Human–computer interaction; Data science; Artificial intelligence; Biology; Genetics; Gene","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":[0.0002596313,0.0001039046,0.0001112503,0.00005070821,0.0001281966,0.0003541646,0.0003722179,0.00005381354,0.00003994725],"category_scores_gemma":[0.0001263427,0.0001002502,0.00005236923,0.0004297649,0.00001799277,0.000480805,0.00005334791,0.00002328396,0.00002663386],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004422665,"about_ca_system_score_gemma":0.00007450655,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001000961,"about_ca_topic_score_gemma":0.00001081713,"domain_scores_codex":[0.9990189,0.00005468093,0.0002434835,0.0002790029,0.000166473,0.0002374769],"domain_scores_gemma":[0.9991938,0.00007266866,0.00007759072,0.000455207,0.0001222839,0.00007846935],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[5.057439e-7,0.00002039443,0.0004009463,0.000008929273,0.000008151686,4.256933e-7,0.00001705122,0.003421813,0.000008584295,0.9770693,0.01018014,0.008863731],"study_design_scores_gemma":[0.0002089221,0.00003497605,0.0007863918,0.0000075785,0.000008525339,0.0000038437,0.00001691765,0.9165465,0.0001650424,0.01108122,0.07096802,0.0001720607],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.000505984,0.0000863716,0.9957603,0.00007638925,0.0002939393,0.0001883954,0.000004601935,0.0001650813,0.002918949],"genre_scores_gemma":[0.1522096,0.0001386997,0.8349836,0.005079273,0.0002801166,0.00005028031,0.0002523356,0.0000507576,0.006955386],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9659881,"threshold_uncertainty_score":0.4088086,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0255191214460969,"score_gpt":0.2929731793355913,"score_spread":0.2674540578894944,"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."}}