{"id":"W7049342643","doi":"","title":"Multi-way correspondence analysis approach to examine Nobel Prize Data from 1901 to 2018","year":2021,"lang":"en","type":"article","venue":"Figshare","topic":"Advanced Measurement and Metrology Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Correspondence analysis; Contingency table; Categorical variable; Association (psychology); Nationality; Multiple correspondence analysis; Multivariate analysis","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00007592305,0.0001779119,0.0002756428,0.0001760299,0.00003824708,0.00003295014,0.0005909955,0.000100391,0.01793149],"category_scores_gemma":[0.001072285,0.0001878266,0.0000536249,0.000941871,0.000002920161,0.000167728,0.0003756043,0.0001525583,0.0009949197],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000594238,"about_ca_system_score_gemma":0.00002048628,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009207649,"about_ca_topic_score_gemma":0.0001358042,"domain_scores_codex":[0.9988182,0.00002832194,0.0001844038,0.0004918939,0.0002010241,0.0002761544],"domain_scores_gemma":[0.9985008,0.00007738428,0.000025022,0.001131471,0.0001000359,0.0001652953],"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":[0.00003220287,0.0001635681,0.0007283129,0.000101681,0.0006205974,0.00005380534,0.0002721871,0.01424451,0.1060519,0.000001507848,0.8665553,0.01117438],"study_design_scores_gemma":[0.0007364569,0.00006925866,0.1036901,0.0005461124,0.0004282114,0.000004998803,0.0001121563,0.1022242,0.09648184,0.00001108749,0.6945181,0.001177348],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.006309752,0.003030526,0.3781619,0.0001066066,0.0003525964,0.001113955,0.5971379,0.002145699,0.01164106],"genre_scores_gemma":[0.1918096,0.00001982791,0.3848966,0.0007812137,0.0002886326,0.0005509208,0.4190224,0.00009460543,0.002536132],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1854999,"threshold_uncertainty_score":0.9997829,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.167871225505988,"score_gpt":0.3073281141530798,"score_spread":0.1394568886470917,"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."}}