{"id":"W2606751029","doi":"10.1142/s0218213017600107","title":"Characterizing Users and Tracking Their Activities in Online Classified Ads","year":2017,"lang":"en","type":"article","venue":"International Journal of Artificial Intelligence Tools","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Profiling (computer programming); Probabilistic logic; User modeling; Set (abstract data type); Class (philosophy); Generative model; Generative grammar; Data mining; Machine learning; User interface; Human–computer interaction; Information retrieval; 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":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0006567915,0.000120139,0.0002252364,0.000264516,0.0001117162,0.001482619,0.001510192,0.00006071569,0.000009086661],"category_scores_gemma":[0.0002133803,0.00009994776,0.00008409111,0.00004498544,0.00007804883,0.002781121,0.0002242868,0.0002718181,0.000001577898],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007325316,"about_ca_system_score_gemma":0.00006180123,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006509866,"about_ca_topic_score_gemma":0.0001142509,"domain_scores_codex":[0.9986996,0.00005440765,0.0006246294,0.0001661711,0.0002983125,0.0001568906],"domain_scores_gemma":[0.9986112,0.0001715634,0.0007055928,0.0002436871,0.0002088757,0.00005906165],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0000367019,0.00009541203,0.00284625,0.000004226982,0.00004112348,0.00008846865,0.001627374,0.00001246515,0.01609925,0.02224075,0.00001941729,0.9568886],"study_design_scores_gemma":[0.0003692629,0.0006461471,0.1390404,0.001854228,0.00001604431,0.001054461,0.006126264,0.04805611,0.6839141,0.1094397,0.008512943,0.0009703811],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7346833,0.00006839466,0.256537,0.006216802,0.001906349,0.00009213155,0.000008933149,0.00002697662,0.0004601278],"genre_scores_gemma":[0.9932263,0.000171841,0.006047725,0.0001647169,0.0003642382,0.000002260302,8.176441e-7,0.00000669947,0.00001544018],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9559182,"threshold_uncertainty_score":0.9995539,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1620729212358601,"score_gpt":0.3655221996245478,"score_spread":0.2034492783886877,"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."}}