{"id":"W2100647638","doi":"10.1145/379437.379722","title":"PERSIVAL, a system for personalized search and summarization over multimedia healthcare information","year":2001,"lang":"en","type":"article","venue":"","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":57,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Automatic summarization; Computer science; Health care; Presentation (obstetrics); World Wide Web; Personalized search; Medical information; Multimedia; Digital library; Personalized medicine; Internet privacy; Information retrieval; Medicine; Search engine","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":[0.001646149,0.0008438488,0.000624041,0.003350751,0.0007404078,0.001724924,0.001116664,0.0008544975,0.006236369],"category_scores_gemma":[0.006422815,0.0004466936,0.0005241625,0.001848288,0.0004568741,0.004197476,0.001910768,0.000809128,0.003002519],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006161724,"about_ca_system_score_gemma":0.001606956,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005643503,"about_ca_topic_score_gemma":0.007001634,"domain_scores_codex":[0.9992545,0.0001435542,0.0001112686,0.00015168,0.0002979464,0.00004100963],"domain_scores_gemma":[0.9984407,0.0006295653,0.000141008,0.0003595262,0.0002931835,0.0001360387],"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":[0.001779689,0.0004322887,0.003488298,0.001605358,0.0003389794,0.0007601961,0.00252143,0.00340406,0.03451274,0.01083791,0.2199661,0.7203529],"study_design_scores_gemma":[0.0007732877,0.0008164169,0.009544913,0.0004033979,0.0006450941,0.002365792,0.002825151,0.1082438,0.07673383,0.03332647,0.7639223,0.0003995862],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.05172713,0.003712013,0.5306262,0.002631807,0.0004411458,0.002431623,0.0251422,0.3451126,0.03817532],"genre_scores_gemma":[0.2378178,0.003292549,0.6547235,0.002947543,0.000435178,0.001473647,0.04886103,0.007064142,0.04338455],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006236369,"threshold_uncertainty_score":0.02086276,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02863656820032564,"score_gpt":0.2813209700394294,"score_spread":0.2526844018391038,"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."}}