{"id":"W2914818188","doi":"10.5555/2872518.3251212","title":"Session details: BigScholar 2015","year":2015,"lang":"en","type":"article","venue":"The Web Conference","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Session (web analytics); Presentation (obstetrics); Library science; Inclusion (mineral); Pleasure; World Wide Web; Big data; Computer science; State (computer science); Political science; Sociology; Psychology; Medicine; Social science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005225276,0.00008326512,0.00007891944,0.00002763483,0.0001332252,0.000313092,0.001544336,0.00003029086,0.00001771494],"category_scores_gemma":[0.00007331407,0.0000524913,0.0000189123,0.0002567569,0.00005510971,0.0004527398,0.0004109629,0.0001426216,0.000726574],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000152869,"about_ca_system_score_gemma":0.000260624,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000575783,"about_ca_topic_score_gemma":0.00001264223,"domain_scores_codex":[0.9992006,0.00006249074,0.0001156411,0.0002270351,0.0002247007,0.0001695525],"domain_scores_gemma":[0.9987484,0.00005166219,0.00005525846,0.000871953,0.000148977,0.000123763],"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":[0.000005162972,0.0001150636,0.0005168808,0.000006197122,0.00001811213,0.000008713369,0.002188586,0.00003393945,0.003967389,0.3848949,0.1521138,0.4561313],"study_design_scores_gemma":[0.0004471211,0.00007647831,0.001526114,0.00004266897,0.0000106488,0.00003594987,0.0002959041,0.4426247,0.001915277,0.02332913,0.5293909,0.0003050052],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02813837,0.0004352217,0.9323171,0.01741603,0.0005165043,0.0002379209,0.00002419313,0.0004223151,0.02049236],"genre_scores_gemma":[0.956323,0.0000335605,0.04200516,0.0004069174,0.00007771669,0.00003153438,0.000006673896,0.000005498167,0.001109971],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9281846,"threshold_uncertainty_score":0.9338881,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07882610516053719,"score_gpt":0.3063348120394692,"score_spread":0.227508706878932,"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."}}