{"id":"W4394828659","doi":"10.1007/978-3-031-58553-1","title":"Advances in Intelligent Data Analysis XXII","year":2024,"lang":"en","type":"book","venue":"Lecture notes in computer science","topic":"Advanced Data Processing Techniques","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Université de Namur; Högskolan i Halmstad; Région Normandie; Université François-Rabelais; Eötvös Loránd Tudományegyetem; Instituto Politécnico do Porto; Universität Mannheim; Masarykova Univerzita; Stockholms Universitet; Universidade do Porto; Université de Caen Normandie; Universidade de Coimbra; Universität Bielefeld; Centre National de la Recherche Scientifique; Université de Strasbourg; Universiteit Gent; Universidade do Minho; Université d'Orléans; Universidad Pública de Navarra; Kungliga Tekniska Högskolan; Télécom Paris; Universiteit Utrecht; KU Leuven; Philipps-Universität Marburg; Forschungszentrum Jülich; Università degli Studi di Torino; Università degli Studi di Trento; Dalhousie University; Deutsches Elektronen-Synchrotron; Technische Universiteit Delft; Institut National des Sciences Appliquées de Lyon; Politechnika Poznańska; University of Bristol; Universidad de Granada; Institut \"Jožef Stefan\"; Universiteit Leiden; Canterbury Christ Church University; Indian National Science Academy; Itä-Suomen Yliopisto; Università degli Studi di Napoli Federico II","keywords":"Computer science","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005618748,0.0003754936,0.0004971487,0.001732408,0.00004044963,0.0002418964,0.003056474,0.0002003687,0.0000104286],"category_scores_gemma":[0.00009570585,0.0003523691,0.00005336122,0.003061866,0.0003269677,0.0009344629,0.001422768,0.0009301323,0.00002219253],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005562659,"about_ca_system_score_gemma":0.0002464732,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006386841,"about_ca_topic_score_gemma":0.00049847,"domain_scores_codex":[0.9974605,0.00001328261,0.0004311738,0.001184939,0.0004657868,0.0004443004],"domain_scores_gemma":[0.9978578,0.0002225513,0.0000593594,0.001755259,0.0000405039,0.00006449098],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[8.021173e-7,0.000005018728,0.0000219921,0.0001385312,0.00001311905,0.00003947253,0.0001049786,0.3911721,0.000008460886,0.00006148337,0.0001352996,0.6082988],"study_design_scores_gemma":[0.0000244232,0.00001492022,0.000007245163,0.0005851671,0.00003608555,0.000004479472,1.454583e-7,0.8838121,0.000725832,0.07815409,0.03622967,0.0004058639],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.000003865474,0.02004475,0.9769492,0.00004043382,0.0007271498,0.0001567942,0.00008233007,0.0005649727,0.001430549],"genre_scores_gemma":[0.01499859,0.007188494,0.9763946,0.0002037926,0.000457575,0.00002279019,0.0005074115,0.00009632374,0.0001304153],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.6078929,"threshold_uncertainty_score":0.9998928,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02039065021001721,"score_gpt":0.3023731519262119,"score_spread":0.2819825017161948,"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."}}