{"id":"W3010893431","doi":"10.1111/1740-9713.01376","title":"Florence Nightingale and Victorian Data Visualisation","year":2020,"lang":"en","type":"article","venue":"Significance","topic":"Census and Population Estimation","field":"Mathematics","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"ECW Press (Canada)","funders":"","keywords":"Beauty; Art history; Power (physics); History; Art; Aesthetics; Physics","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.007546341,0.0005458164,0.0005761138,0.002918538,0.002407337,0.006907171,0.001145447,0.001962345,0.04846741],"category_scores_gemma":[0.04129202,0.0007088177,0.0004896762,0.002532,0.002715937,0.005922832,0.004068764,0.004116686,0.01265976],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003542236,"about_ca_system_score_gemma":0.003218898,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06698021,"about_ca_topic_score_gemma":0.08253899,"domain_scores_codex":[0.9939042,0.002094113,0.0002288971,0.0007603901,0.002724466,0.0002878437],"domain_scores_gemma":[0.981683,0.009057418,0.000330344,0.002039556,0.005620638,0.001269027],"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":[0.00002757003,0.000009255426,0.000475336,0.0000896749,0.000006527831,0.00006662987,0.0009828702,0.0002479588,0.0002893922,0.01935505,0.9176483,0.06080156],"study_design_scores_gemma":[0.000005183474,0.000003939822,0.0003112385,0.0001630205,0.00000243008,0.00007384748,0.0003128392,0.0006155521,0.0002618845,0.007311951,0.9909198,0.00001840153],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.006765213,0.02714629,0.06948336,0.6089508,0.02114747,0.0001758354,0.00475762,0.01276019,0.2488134],"genre_scores_gemma":[0.1320592,0.02706951,0.09215639,0.05816681,0.006583049,0.0004155575,0.003435844,0.01717116,0.6629426],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9975927,"threshold_uncertainty_score":0.1621396,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2041803124288068,"score_gpt":0.3723379529224176,"score_spread":0.1681576404936108,"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."}}