{"id":"W2489962730","doi":"10.4135/9780857020994.n11","title":"Correspondence Analysis, Multiple Correspondence Analysis, and Recent Developments","year":2009,"lang":"en","type":"book-chapter","venue":"","topic":"Sensory Analysis and Statistical Methods","field":"Agricultural and Biological Sciences","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Correspondence analysis; Correspondence problem; Computer science; Artificial intelligence; Machine learning","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":[],"category_scores_codex":[0.0008188463,0.0005810712,0.001385483,0.0002985653,0.0003193231,0.000197246,0.0004678608,0.0004592452,0.01868398],"category_scores_gemma":[0.0004251995,0.0002376992,0.0006064925,0.001558739,0.0001724791,0.00009347379,0.000148451,0.0004054543,0.0001701282],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006924932,"about_ca_system_score_gemma":0.00002512518,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001691133,"about_ca_topic_score_gemma":0.00434719,"domain_scores_codex":[0.9965148,0.0002172622,0.000825316,0.001222292,0.00075971,0.0004606454],"domain_scores_gemma":[0.9967579,0.001899941,0.0004109782,0.0002233926,0.0003065319,0.0004012164],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0002324415,0.00007134315,0.01077778,0.00000593416,0.004851812,0.00009244186,0.00003358556,0.00004138456,0.001992353,0.007677982,0.00100817,0.9732147],"study_design_scores_gemma":[0.0001729561,0.0002602485,0.5545409,0.00003818069,0.01125286,0.000008645837,0.0000484132,0.002903549,0.0002181986,0.004596015,0.4245939,0.001366209],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.05726598,0.0059878,0.02368633,0.002109337,0.0007526462,0.001969092,0.001870127,0.0007299563,0.9056287],"genre_scores_gemma":[0.04425071,0.003292118,0.01438873,0.001250765,0.0001607501,0.0000101613,0.001113072,0.000004516017,0.9355292],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.9718485,"threshold_uncertainty_score":0.9822131,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04570318121514966,"score_gpt":0.2753284010049897,"score_spread":0.2296252197898401,"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."}}