{"id":"W2165706283","doi":"10.5555/602099.602136","title":"GeneVis: visualization tools for genetic regulatory network dynamics","year":2002,"lang":"en","type":"article","venue":"IEEE Visualization","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Visualization; Computer science; Focus (optics); Process (computing); Information visualization; Data visualization; Human–computer interaction; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003350809,0.0002678473,0.000258959,0.0002116292,0.0003409796,0.0007394743,0.0007032331,0.0001692096,0.00007004966],"category_scores_gemma":[0.0002175656,0.0002935492,0.0001139787,0.00133718,0.00004813795,0.001401758,0.00008715878,0.00005494743,0.00009647272],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001526701,"about_ca_system_score_gemma":0.00004329881,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003042363,"about_ca_topic_score_gemma":0.00002119317,"domain_scores_codex":[0.9976988,0.0001368887,0.0006241024,0.0006089362,0.0004678579,0.000463395],"domain_scores_gemma":[0.9982458,0.0001793541,0.0003231802,0.0007278001,0.0003741368,0.0001497647],"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":[0.0000147294,0.0002272309,0.0006865686,0.00009696436,0.00006511943,0.000002926197,0.0003645511,0.02851354,0.000194968,0.8624535,0.05478643,0.05259344],"study_design_scores_gemma":[0.0007344694,0.0001419322,0.0005370388,0.00003673583,0.00003405659,0.000004001024,0.00001819664,0.9747264,0.0003717244,0.001492919,0.02153098,0.0003715271],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002479714,0.0002516404,0.9940877,0.0001295273,0.001556455,0.0005085175,0.00002677727,0.0005022907,0.0004573919],"genre_scores_gemma":[0.8587672,0.001655895,0.1226884,0.005101184,0.003529661,0.0003515558,0.002441021,0.0003297333,0.00513539],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9462129,"threshold_uncertainty_score":0.9999517,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03905607807491299,"score_gpt":0.3019224198744776,"score_spread":0.2628663417995646,"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."}}