{"id":"W1973206570","doi":"10.1016/j.dss.2007.05.006","title":"Website browsing aid: A navigation graph-based recommendation system","year":2007,"lang":"en","type":"article","venue":"Decision Support Systems","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":45,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"China Scholarship Council; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China; University of Washington","keywords":"Computer science; Recommender system; Information overload; Graph; World Wide Web; Navigation system; Information retrieval; Real-time computing","routes":{"ca_aff":true,"ca_fund":true,"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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.005096423,0.0003197778,0.0004859633,0.000710035,0.0003384393,0.0006735127,0.0008474056,0.0002468315,0.0000230354],"category_scores_gemma":[0.00003675853,0.0002864633,0.0001984938,0.001058304,0.00002377345,0.0009945361,0.0001480038,0.0002152666,0.0002568454],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003361115,"about_ca_system_score_gemma":0.00009908171,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002516806,"about_ca_topic_score_gemma":0.00001690265,"domain_scores_codex":[0.9962051,0.0002107806,0.001435148,0.0007688715,0.0008280309,0.0005520482],"domain_scores_gemma":[0.9972243,0.0004363184,0.0006625485,0.001071623,0.0003461215,0.0002590402],"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":[0.0001827998,0.0004025298,0.01866673,0.001039435,0.000148887,0.0006494864,0.001412221,0.0002881425,0.004046827,0.08912651,0.1019211,0.7821153],"study_design_scores_gemma":[0.003797352,0.0008260941,0.004641398,0.003505667,0.00005001386,0.001954466,0.001549189,0.2168606,0.0125926,0.001671356,0.7504327,0.002118541],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008169655,0.00008148891,0.9776292,0.0001448553,0.00378953,0.0007554896,0.00001026811,0.001190611,0.008228933],"genre_scores_gemma":[0.9503499,0.000002710236,0.04895471,0.0001355734,0.0002189435,0.00006035306,0.00008332317,0.0000339675,0.000160482],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9421803,"threshold_uncertainty_score":0.9999588,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02553002171818773,"score_gpt":0.291850017953823,"score_spread":0.2663199962356352,"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."}}