{"id":"W1536212463","doi":"10.1007/978-3-540-77092-3_43","title":"Extraction and Classification of User Behavior","year":2007,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Management and Algorithms","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"St. Francis Xavier University","funders":"Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; Fundação de Amparo à Pesquisa do Estado de São Paulo","keywords":"Computer science; Markov chain; Generator (circuit theory); Artificial neural network; User group; Artificial intelligence; Human–computer interaction; Machine learning; Multimedia; Power (physics)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005558984,0.0007818755,0.0007403091,0.005550065,0.0004421599,0.001115217,0.0006106758,0.0005707045,0.003088875],"category_scores_gemma":[0.002313534,0.000211539,0.0008359298,0.003266457,0.000180416,0.00102886,0.0005128185,0.0005889391,0.004855417],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003584983,"about_ca_system_score_gemma":0.0006777857,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005793841,"about_ca_topic_score_gemma":0.01060545,"domain_scores_codex":[0.9992959,0.0001176874,0.00006582003,0.0001826593,0.0002407316,0.00009702702],"domain_scores_gemma":[0.998455,0.0006350846,0.0001554177,0.0002139418,0.0004345035,0.0001059671],"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":[0.0004283855,0.0004570397,0.07500917,0.0004246838,0.0001087459,0.0002139203,0.0004424473,0.001447494,0.03041914,0.001634471,0.0216342,0.8677803],"study_design_scores_gemma":[0.00006531375,0.0008441558,0.4502545,0.0004778677,0.0005052702,0.002851779,0.001827003,0.3545572,0.0977488,0.01273752,0.07790703,0.0002236753],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.4365563,0.004407364,0.4583153,0.00115921,0.0003911239,0.0008974774,0.05398057,0.02057411,0.02371855],"genre_scores_gemma":[0.6807595,0.001882451,0.2416817,0.0001997382,0.0002784829,0.0004488246,0.05043755,0.000510861,0.02380075],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005793841,"threshold_uncertainty_score":0.01152021,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04153065881389877,"score_gpt":0.2941857990500126,"score_spread":0.2526551402361139,"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."}}