{"id":"W2767015367","doi":"","title":"Stacking With Auxiliary Features for Combining Supervised and Unsupervised Ensembles","year":2016,"lang":"en","type":"article","venue":"Theory and applications of categories","topic":"Industrial Vision Systems and Defect Detection","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Stacking; Computer science; Artificial intelligence; Pattern recognition (psychology); Machine learning; Chemistry","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002659178,0.00009055942,0.0001425312,0.00005620068,0.0001452538,0.00002211548,0.00004168847,0.00005894884,0.000005154674],"category_scores_gemma":[0.00001598494,0.00005755813,0.00001689802,0.00008072677,0.000105305,0.0001025049,0.00001071201,0.00003533677,5.372405e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000005969398,"about_ca_system_score_gemma":0.000008963297,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005542425,"about_ca_topic_score_gemma":0.000003275915,"domain_scores_codex":[0.9995924,0.00002496583,0.0001304613,0.0001076307,0.0000503005,0.00009430194],"domain_scores_gemma":[0.999382,0.0003758088,0.00002762306,0.0001269863,0.00005431623,0.00003332383],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004477826,0.00001768426,0.0004936752,0.0003108724,0.00009316046,2.465403e-7,0.001125455,0.00006924365,0.09910187,0.6666089,0.0001511856,0.2315799],"study_design_scores_gemma":[0.006796301,0.0007528561,0.003613695,0.0004948837,0.0002345461,0.00007098565,0.01038969,0.0003966894,0.625063,0.3197133,0.03143779,0.001036266],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8010693,0.001095559,0.1960151,0.00005019306,0.00004734355,0.0006040349,0.00004062611,0.0001526644,0.0009252616],"genre_scores_gemma":[0.9992925,0.00008187346,0.0002397224,0.000006062528,0.00006131895,0.0001781611,0.000004140784,0.00001564239,0.000120562],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5259611,"threshold_uncertainty_score":0.2347153,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01001161706614145,"score_gpt":0.2213674018845962,"score_spread":0.2113557848184547,"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."}}