{"id":"W4235343288","doi":"10.32920/ryerson.14653989.v1","title":"Financial data visualization based on power-law degree distribution","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Complex Systems and Time Series Analysis","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Visualization; Computer science; Degree distribution; Zoom; Scalability; Complex network; Data mining; Data visualization; Node (physics); Theoretical computer science; Database; Engineering","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":[0.0009459183,0.0006122374,0.0003718664,0.002460007,0.0005660092,0.00192709,0.0007263864,0.0005702826,0.005508767],"category_scores_gemma":[0.006700187,0.0003554989,0.0005495696,0.001813353,0.0004720251,0.003468595,0.001261843,0.00102876,0.0009171221],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008745177,"about_ca_system_score_gemma":0.0005924126,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002516367,"about_ca_topic_score_gemma":0.002577652,"domain_scores_codex":[0.9994901,0.000159038,0.00003378928,0.0001045692,0.0001681419,0.00004426134],"domain_scores_gemma":[0.9971164,0.001601063,0.000253775,0.0003309936,0.0005607397,0.0001370892],"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":[0.0004921101,0.0001625682,0.01647128,0.0007751065,0.0001361906,0.0006518522,0.002886852,0.2145649,0.05043191,0.1705503,0.03972305,0.5031539],"study_design_scores_gemma":[0.00004859132,0.00005023092,0.003662536,0.00006139601,0.00002789856,0.0003821019,0.0003069823,0.8833341,0.01808654,0.06647743,0.02750354,0.00005860359],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0447587,0.000409666,0.9408654,0.0007932848,0.00007368417,0.00008495049,0.0008032859,0.006370057,0.00584099],"genre_scores_gemma":[0.5513877,0.001502426,0.4383465,0.0002280847,0.00008552772,0.0002194403,0.001535643,0.001425594,0.005268998],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005508767,"threshold_uncertainty_score":0.01842868,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1023968436343548,"score_gpt":0.2678236164838656,"score_spread":0.1654267728495108,"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."}}