{"id":"W2120855387","doi":"10.1109/waim.2008.62","title":"PLEDS: A Personalized Entity Detection System Based on Web Log Mining Techniques","year":2008,"lang":"en","type":"article","venue":"","topic":"Web Data Mining and Analysis","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; The Internet; World Wide Web; Theme (computing); Web mining; Subject (documents); Internet users; Subject matter; Data science; Web page","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":[0.001374021,0.0009396211,0.000911234,0.004426342,0.0005975662,0.001137498,0.001503146,0.0006947672,0.004065148],"category_scores_gemma":[0.005430502,0.0006596841,0.0005476646,0.002095985,0.000336089,0.003634803,0.001772183,0.0009437163,0.003263665],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003652237,"about_ca_system_score_gemma":0.0006538018,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00236356,"about_ca_topic_score_gemma":0.004651806,"domain_scores_codex":[0.9991416,0.0001624415,0.0001014825,0.0002623222,0.0002924513,0.00003973032],"domain_scores_gemma":[0.9972569,0.001226795,0.0003251789,0.0006690781,0.0003174288,0.0002046281],"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":[0.002028171,0.0008070397,0.02459748,0.0009224159,0.0004878688,0.001129086,0.0007314474,0.006155693,0.04543309,0.003328196,0.1490968,0.7652828],"study_design_scores_gemma":[0.0007185885,0.001043766,0.04556988,0.000175304,0.0005217304,0.003557003,0.0006555158,0.6093964,0.1140722,0.0137812,0.2100462,0.0004623426],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07680529,0.0008130905,0.5572506,0.0007201339,0.0001833301,0.001174151,0.02472234,0.3339438,0.004387223],"genre_scores_gemma":[0.291733,0.0007461737,0.6393024,0.0007209562,0.0001782625,0.0009246616,0.04904468,0.00266103,0.01468889],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004426342,"threshold_uncertainty_score":0.01359928,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0203775830950886,"score_gpt":0.2289175758069761,"score_spread":0.2085399927118875,"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."}}