{"id":"W1991981269","doi":"10.1145/1531674.1531688","title":"Personalized retrieval in social bookmarking","year":2009,"lang":"en","type":"article","venue":"","topic":"Spam and Phishing Detection","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Bookmarking; Computer science; Ranking (information retrieval); Relevance (law); World Wide Web; Information retrieval; Order (exchange); Selection (genetic algorithm); Learning to rank; Artificial intelligence","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":[0.002570477,0.0006277831,0.001290119,0.004594609,0.001541393,0.002364507,0.001211633,0.001492161,0.002364621],"category_scores_gemma":[0.01023938,0.0007164976,0.0005113741,0.003736116,0.001110455,0.004517098,0.001541068,0.00081503,0.00173678],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00126968,"about_ca_system_score_gemma":0.001044539,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005021688,"about_ca_topic_score_gemma":0.00822248,"domain_scores_codex":[0.9976387,0.0007834719,0.0001202673,0.0004497762,0.0007479528,0.0002598836],"domain_scores_gemma":[0.9936364,0.002726224,0.0007156474,0.001796901,0.0008938796,0.0002310557],"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":[0.00060484,0.0009835267,0.02513248,0.0005127237,0.0001988972,0.0008192864,0.002008603,0.07700797,0.02496441,0.03403891,0.01392949,0.8197988],"study_design_scores_gemma":[0.0001454048,0.0005449536,0.02104548,0.00007085917,0.0002033631,0.001859646,0.0009733195,0.8480977,0.02596476,0.0749465,0.02597188,0.0001762406],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.3509234,0.003538162,0.6232267,0.001008382,0.0001118445,0.000639685,0.0004711334,0.005524568,0.01455622],"genre_scores_gemma":[0.7987881,0.000970807,0.1874558,0.0002240756,0.000287127,0.000174605,0.000561722,0.0002240829,0.01131368],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005021688,"threshold_uncertainty_score":0.01359415,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02147225152857814,"score_gpt":0.2623921892942219,"score_spread":0.2409199377656437,"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."}}