{"id":"W2913556077","doi":"","title":"Proceedings of the 25th International Conference on World Wide Web","year":2016,"lang":"en","type":"article","venue":"","topic":"Web Data Mining and Analysis","field":"Computer Science","cited_by":635,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal; Université TÉLUQ","funders":"","keywords":"Computer science; World Wide Web; Track (disk drive); Social media; Consistency (knowledge bases); Personalization; Phishing; Data science; The Internet","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":[0.003263557,0.001665303,0.002333171,0.002737648,0.001465721,0.009391792,0.002019842,0.002376351,0.1468257],"category_scores_gemma":[0.008963847,0.0005060015,0.001051105,0.002789654,0.001136092,0.01021781,0.003375754,0.003768871,0.1359949],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009459822,"about_ca_system_score_gemma":0.002246858,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001824705,"about_ca_topic_score_gemma":0.002499146,"domain_scores_codex":[0.9965071,0.0008328085,0.000334178,0.0006074866,0.001365594,0.0003527438],"domain_scores_gemma":[0.9933648,0.001370663,0.0003167014,0.001275816,0.00241857,0.001253553],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008432579,0.0001076978,0.0006485438,0.0005566505,0.00006197642,0.0001700268,0.0001201776,0.0001257967,0.001833711,0.004439402,0.7940987,0.197753],"study_design_scores_gemma":[0.000008182868,0.00003366674,0.0008641682,0.0002261705,0.00002600145,0.0002354255,0.0001332308,0.0006980333,0.0004923221,0.003542114,0.9937196,0.00002096649],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.01498295,0.1494487,0.1073816,0.0452598,0.1682955,0.001686197,0.01974892,0.01765665,0.4755397],"genre_scores_gemma":[0.03963891,0.07584099,0.04264375,0.01138801,0.025027,0.0009412225,0.04931273,0.004014378,0.7511929],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.1468257,"threshold_uncertainty_score":0.4911811,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0271719921717674,"score_gpt":0.2464222719911995,"score_spread":0.2192502798194321,"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."}}