{"id":"W2912769923","doi":"10.1111/j.1740-9713.2019.01229.x","title":"Visualising the<i>Titanic</i>Disaster","year":2019,"lang":"en","type":"article","venue":"Significance","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Tragedy (event); History; Visualization; Data science; Computer science; Literature; Art; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008385761,0.0004359993,0.0002481567,0.00242839,0.0004300915,0.002849664,0.0006173913,0.0007888505,0.01124467],"category_scores_gemma":[0.003879242,0.0002308036,0.0002768188,0.002717808,0.0008795136,0.002830748,0.0009875308,0.001196045,0.002872707],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008185433,"about_ca_system_score_gemma":0.0007870038,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004198086,"about_ca_topic_score_gemma":0.0075408,"domain_scores_codex":[0.9996486,0.00008394138,0.00001581634,0.00004331577,0.0001813028,0.0000270273],"domain_scores_gemma":[0.9979818,0.001013336,0.0001779291,0.0001009012,0.0006114661,0.0001144807],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006297546,0.00001686783,0.002121395,0.004762945,0.00006863882,0.0005312838,0.002203949,0.003848879,0.004109723,0.04726882,0.5836523,0.3513522],"study_design_scores_gemma":[0.000004505167,0.00001457183,0.001472168,0.0007977231,0.00001846949,0.0004183624,0.0007296078,0.0009115733,0.001092833,0.01319497,0.9813216,0.0000237291],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.03312667,0.4471594,0.1471965,0.1020319,0.01649117,0.0002571593,0.005755282,0.008015417,0.2399666],"genre_scores_gemma":[0.3301635,0.4329785,0.09031704,0.01218679,0.01100216,0.0002246864,0.00689416,0.00364676,0.1125864],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01124467,"threshold_uncertainty_score":0.03761715,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01568433044093996,"score_gpt":0.2773413171302379,"score_spread":0.2616569866892979,"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."}}