{"id":"W2920554262","doi":"10.5555/2872518.3251216","title":"Session details: OD4LS'16","year":2016,"lang":"en","type":"article","venue":"The Web Conference","topic":"Web Data Mining and Analysis","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Computer science; World Wide Web; USable; Semantic search; Service (business); Session (web analytics); Geolocation; Semantic Web; Data science; Information retrieval","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003841101,0.0001010828,0.0001167913,0.00004687471,0.0001428249,0.0001065771,0.001613658,0.00003325622,0.0001817774],"category_scores_gemma":[0.0001003005,0.00004449867,0.00004951239,0.0002306042,0.00008726795,0.0003761722,0.0003895932,0.00007051432,0.0007719902],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001993128,"about_ca_system_score_gemma":0.0001294963,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003865271,"about_ca_topic_score_gemma":0.00004673621,"domain_scores_codex":[0.9990237,0.0001101419,0.0001383763,0.0002839274,0.0002184453,0.0002253888],"domain_scores_gemma":[0.9986165,0.0001973287,0.00007136464,0.0009741514,0.00007176067,0.00006893659],"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":[0.000006907644,0.00004512823,0.003712017,0.000006706057,0.00004446235,0.000008779957,0.0005018135,0.000001966107,0.0497374,0.1825316,0.01077307,0.7526301],"study_design_scores_gemma":[0.004174578,0.0005340427,0.03825274,0.001786884,0.0002503672,0.0001776702,0.000926238,0.1702013,0.126269,0.134926,0.5193633,0.003137745],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1086156,0.00009032538,0.861214,0.01665934,0.0002591146,0.00006895082,0.000008757762,0.0002660736,0.01281786],"genre_scores_gemma":[0.994695,0.00007324899,0.001462439,0.0002778877,0.00005375088,0.000006632685,9.898954e-7,0.000003916035,0.003426131],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8860794,"threshold_uncertainty_score":0.992263,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03571743253908267,"score_gpt":0.2535780763176482,"score_spread":0.2178606437785656,"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."}}