{"id":"W4412767561","doi":"10.23952/jano.7.2025.2.01","title":"Some notes about a relative order relation used in unsupervised deep learning","year":2025,"lang":"en","type":"article","venue":"Journal of Applied and Numerical Optimization","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Relation (database); Order (exchange); Artificial intelligence; Unsupervised learning; Psychology; Computer science; Natural language processing; Cognitive psychology; Data mining; Economics","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":[0.0001805595,0.00008549637,0.0001800293,0.0001596667,0.0001053115,0.00007800936,0.0001451475,0.00006661305,0.000004136901],"category_scores_gemma":[0.00004960595,0.00007227386,0.00003135682,0.000769736,0.00002245184,0.0004759981,0.00004851693,0.0002807112,0.000001185821],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000328018,"about_ca_system_score_gemma":0.00003266473,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002299138,"about_ca_topic_score_gemma":3.115769e-7,"domain_scores_codex":[0.9992067,0.00003883986,0.0003600768,0.0001500532,0.0001303516,0.0001139695],"domain_scores_gemma":[0.9993387,0.0002302058,0.0002126245,0.00008174571,0.00008854525,0.00004820523],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002717422,0.00004487083,0.0007704765,0.00000450594,0.00001035288,0.000001348513,0.0002935739,0.8944923,0.0002926805,0.08445933,0.00001038023,0.019593],"study_design_scores_gemma":[0.0006530157,0.00005022129,0.00538929,0.00003565028,0.00001088582,0.000002720365,0.00002590703,0.9793088,0.0001100835,0.01402611,0.0003048941,0.0000823883],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008149925,0.0002633803,0.9892315,0.001646268,0.00005976818,0.0001123032,9.018824e-8,0.00001982053,0.0005169202],"genre_scores_gemma":[0.8605562,0.0003165896,0.1387926,0.0002467743,0.00005168294,0.000006659172,0.000002038257,0.000005081663,0.00002226341],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8524063,"threshold_uncertainty_score":0.2947243,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007976941909530213,"score_gpt":0.236763456951014,"score_spread":0.2287865150414838,"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."}}