{"id":"W2912892171","doi":"10.1145/3252653","title":"Session details: Session 3","year":2016,"lang":"en","type":"article","venue":"","topic":"Diverse Scientific and Economic Studies","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Session (web analytics); Computer science; World Wide Web","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.002022506,0.001337533,0.001694554,0.0009098671,0.002743019,0.00663606,0.001691901,0.004401904,0.9154709],"category_scores_gemma":[0.005841298,0.0004295598,0.001561198,0.0007768584,0.0003422894,0.002670405,0.003160111,0.003803659,0.8313508],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001505202,"about_ca_system_score_gemma":0.002227194,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002157927,"about_ca_topic_score_gemma":0.004746317,"domain_scores_codex":[0.9991783,0.0001316766,0.00004211632,0.0002153073,0.0002397635,0.0001927341],"domain_scores_gemma":[0.9959555,0.0004518617,0.0001168963,0.0003365294,0.001426604,0.001712638],"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":[0.0001416876,0.0000319471,0.00004374884,0.000106477,0.000005121065,0.0000185406,0.00001325704,0.00002166115,0.00018889,0.0004446029,0.986999,0.01198508],"study_design_scores_gemma":[0.0000539646,0.00004145327,0.0003009818,0.00009386577,0.000006940922,0.00003138031,0.00003759057,0.0000547346,0.0001660209,0.0006835447,0.9985197,0.000009761318],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.001231938,0.002897016,0.003438513,0.01691697,0.08988141,0.001870307,0.0272156,0.006509066,0.8500392],"genre_scores_gemma":[0.004863551,0.001154358,0.0007601038,0.003972881,0.008037136,0.0006412412,0.007160543,0.001575239,0.971835],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.0845291,"threshold_uncertainty_score":0.1205705,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04981601386353313,"score_gpt":0.2171701386244437,"score_spread":0.1673541247609106,"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."}}