{"id":"W2550508329","doi":"10.1145/2992154.2996873","title":"Exploring Genetic Mutations on Mitochondrial DNA Cancer Data with Interactive Tabletop and Active Tangibles","year":2016,"lang":"en","type":"article","venue":"","topic":"Scientific Computing and Data Management","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Foundation for Innovation","keywords":"Computer science; Mitochondrial DNA; Human–computer interaction; Data science; DNA sequencing; DNA; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001337684,0.001031678,0.0005490141,0.001200181,0.0004078273,0.001632695,0.00130073,0.0007787169,0.0172333],"category_scores_gemma":[0.005353743,0.0004243612,0.0009404066,0.0009254938,0.0005169893,0.001179895,0.00304891,0.0005353191,0.001229731],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003762502,"about_ca_system_score_gemma":0.0004506329,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00189649,"about_ca_topic_score_gemma":0.003362391,"domain_scores_codex":[0.9992377,0.0002560549,0.00005201506,0.0001772319,0.000209548,0.00006750007],"domain_scores_gemma":[0.9946541,0.004365776,0.0001825269,0.000374859,0.0001780941,0.0002447627],"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":[0.006567661,0.0007889198,0.0180098,0.002478197,0.0004828843,0.006041738,0.007983915,0.04243926,0.08469638,0.005952419,0.02948887,0.79507],"study_design_scores_gemma":[0.003360452,0.006399733,0.09389435,0.001415774,0.001033468,0.007200482,0.008104688,0.578015,0.09428717,0.03828934,0.1669277,0.00107182],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5386898,0.002300205,0.419032,0.00144647,0.0002431839,0.0008516175,0.00696982,0.01388908,0.01657784],"genre_scores_gemma":[0.669427,0.001235927,0.3202918,0.0003033818,0.00008645588,0.000736867,0.002618008,0.0004574554,0.004843094],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0172333,"threshold_uncertainty_score":0.05765104,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3774913862688897,"score_gpt":0.4077064402910216,"score_spread":0.03021505402213187,"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."}}