{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001983068,0.00006375088,0.00009388596,0.00008073045,0.0001206321,0.000148611,0.000154744,0.00004917698,0.000005129302],"category_scores_gemma":[0.00004370699,0.00005129229,0.00002559784,0.000132049,0.00002499907,0.000799779,0.00005965416,0.00003315863,0.000009415631],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004226972,"about_ca_system_score_gemma":0.00004758035,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003895145,"about_ca_topic_score_gemma":0.00004442815,"domain_scores_codex":[0.9993933,0.00002817948,0.0001289054,0.0001231338,0.0001587887,0.000167717],"domain_scores_gemma":[0.9995657,0.00009217882,0.00002754874,0.0001352637,0.0001239468,0.00005533269],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001439429,0.00004329803,0.05992639,0.0009969987,0.0000469961,0.000007721432,0.02322061,0.00007421331,0.0002852175,0.6895877,0.003151849,0.222515],"study_design_scores_gemma":[0.001392392,0.0001125433,0.02269468,0.00003970444,0.000005556861,0.00003817474,0.004396563,0.96445,0.0002361913,0.0001544518,0.006324846,0.0001548762],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07016248,0.0001467399,0.9250487,0.002954869,0.0002060333,0.0004298438,0.000003268651,0.0002261562,0.0008219276],"genre_scores_gemma":[0.9575527,0.00004986653,0.0415339,0.0004324616,0.00003812618,0.00002502229,0.00001646915,0.000002965676,0.0003484515],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9643758,"threshold_uncertainty_score":0.2091639,"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."}}