{"id":"W4253515722","doi":"10.1002/9781118445112.stat00425.pub2","title":"Mosaic Displays","year":2015,"lang":"en","type":"other","venue":"Wiley StatsRef: Statistics Reference Online","topic":"Sensory Analysis and Statistical Methods","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Mosaic; Categorical variable; Log-linear model; Statistics; Independence (probability theory); Conditional independence; Mathematics; Shading; Econometrics; Computer science; Geography; Computer graphics (images); Linear model","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003193391,0.0006208159,0.0009570994,0.00006579308,0.0001247384,0.0001072611,0.000580464,0.0004741918,0.01835878],"category_scores_gemma":[0.0006171366,0.0002557205,0.00009059118,0.0005243396,0.0002384414,0.0000405814,0.0001469609,0.0005845652,0.0005435874],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006711428,"about_ca_system_score_gemma":0.00007054726,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001177514,"about_ca_topic_score_gemma":0.009579604,"domain_scores_codex":[0.9966926,0.0003788522,0.0006240126,0.00085482,0.0007888855,0.0006608533],"domain_scores_gemma":[0.9978279,0.0006626491,0.0004432366,0.0002607839,0.000267214,0.0005382427],"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":[0.00002629575,0.0002213349,0.00004823388,0.00003597525,0.0000908884,0.00006406693,0.0000117419,0.000002071314,0.0003035311,0.007845397,0.8795495,0.111801],"study_design_scores_gemma":[0.0001783735,0.0003206814,0.0003312227,0.0001641367,0.00016945,0.00000610162,0.00009854433,0.0005614088,0.000004512643,0.01007603,0.9874171,0.0006724122],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.0003052237,0.004233696,0.02005248,0.0005277926,0.001128617,0.00100446,0.6726565,0.0009033534,0.2991878],"genre_scores_gemma":[0.0002583862,0.002922788,0.2041797,0.0004422557,0.001420126,0.00003131227,0.08939447,0.00008008839,0.7012708],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.5832621,"threshold_uncertainty_score":0.9999895,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08539752937857514,"score_gpt":0.329974455486878,"score_spread":0.2445769261083028,"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."}}