{"id":"W1603350713","doi":"10.1007/978-3-642-02247-0","title":"User modeling, adaptation, and personalization : 17th international conference, UMAP 2009, formerly UM and AH, Trento, Italy, June 22-26, 2009 : proceedings","year":2009,"lang":"en","type":"article","venue":"","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Computer science; Personalization; User modeling; Adaptation (eye); Adaptive hypermedia; World Wide Web; Library science; Hypermedia; User interface; Programming language","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":[0.01067868,0.001239906,0.002812074,0.001552596,0.001257907,0.005015505,0.002181014,0.002122968,0.00633037],"category_scores_gemma":[0.009713025,0.00114659,0.001251507,0.002561915,0.001438677,0.007445575,0.002660775,0.003670768,0.002920116],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001456401,"about_ca_system_score_gemma":0.002113829,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01016103,"about_ca_topic_score_gemma":0.01231551,"domain_scores_codex":[0.9971395,0.001105595,0.0002093677,0.0007143213,0.0006584817,0.0001728491],"domain_scores_gemma":[0.994327,0.002323528,0.0001548379,0.001207426,0.001514555,0.0004727737],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004502181,0.0005332383,0.004085281,0.0004584451,0.0002512436,0.0001465714,0.001087251,0.004926554,0.004308574,0.01086632,0.1470863,0.8258],"study_design_scores_gemma":[0.0001564249,0.0009037005,0.02403145,0.00088986,0.0007994089,0.001937276,0.002501722,0.3756923,0.01785309,0.05777648,0.5171528,0.000305462],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.03338451,0.09491874,0.8335152,0.01591437,0.006042381,0.0004453807,0.0008348863,0.005149723,0.009794877],"genre_scores_gemma":[0.2488221,0.07029364,0.5740569,0.00180812,0.006703034,0.0005003111,0.005010041,0.001544026,0.09126171],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.01067868,"threshold_uncertainty_score":0.05647492,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03227790305649857,"score_gpt":0.2608086255656747,"score_spread":0.2285307225091761,"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."}}