{"id":"W2887408259","doi":"","title":"Toward Session Consistency for the Edge","year":2018,"lang":"en","type":"article","venue":"","topic":"Team Dynamics and Performance","field":"Psychology","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Session (web analytics); Consistency (knowledge bases); Computer science; Enhanced Data Rates for GSM Evolution; Artificial intelligence; 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":[],"consensus_categories":[],"category_scores_codex":[0.05427443,0.0005338177,0.00111317,0.001741976,0.002907878,0.005711968,0.00347545,0.002354403,0.007808734],"category_scores_gemma":[0.1930799,0.0008532961,0.0007428026,0.001109443,0.002744589,0.00797544,0.007550967,0.004778886,0.001656419],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001653168,"about_ca_system_score_gemma":0.00426252,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00192556,"about_ca_topic_score_gemma":0.002032671,"domain_scores_codex":[0.9688871,0.01880675,0.001017212,0.005061029,0.004604344,0.001623562],"domain_scores_gemma":[0.777696,0.127801,0.01439402,0.04699399,0.02649923,0.006615687],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.006878185,0.002157159,0.1590664,0.0006439844,0.0005286366,0.0001396507,0.01843822,0.01445269,0.008064178,0.2627275,0.01648023,0.5104231],"study_design_scores_gemma":[0.000708297,0.002219283,0.1695504,0.0008096245,0.0004373035,0.0003732029,0.0109044,0.1206724,0.01181093,0.6515498,0.03070723,0.0002571241],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4687715,0.001087269,0.4280793,0.01333843,0.0006440462,0.0005011767,0.0008214377,0.001642573,0.08511421],"genre_scores_gemma":[0.9330877,0.0001059304,0.06102296,0.001247477,0.0002037759,0.000257494,0.0002705053,0.0003877153,0.003416422],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05427443,"threshold_uncertainty_score":0.287034,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06267783388368411,"score_gpt":0.3568988631297066,"score_spread":0.2942210292460224,"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."}}