{"id":"W2014772392","doi":"10.1007/s11042-010-0703-z","title":"Improving online gaming experience using location awareness and interaction details","year":2011,"lang":"en","type":"article","venue":"Multimedia Tools and Applications","topic":"Peer-to-Peer Network Technologies","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Quality of experience; Latency (audio); Human–computer interaction; Set (abstract data type); Orientation (vector space); Constraint (computer-aided design); Computer network; Quality of service; Telecommunications","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":[],"consensus_categories":[],"category_scores_codex":[0.0000826246,0.000108975,0.0001023481,0.00009704832,0.000216619,0.0001335593,0.0003214385,0.00005761861,0.000001787372],"category_scores_gemma":[0.00006605701,0.0001078839,0.00001139347,0.0003768376,0.00007181874,0.0006565736,0.0002998191,0.00009298615,0.000004553564],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003177403,"about_ca_system_score_gemma":0.0000256592,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002084093,"about_ca_topic_score_gemma":0.00004638644,"domain_scores_codex":[0.9991652,0.00001155241,0.0001790234,0.0003764274,0.00008975394,0.0001780154],"domain_scores_gemma":[0.9993054,0.00007055712,0.00008703314,0.0003669726,0.00009079774,0.00007923476],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000001747594,0.00004237133,0.003194194,0.00001139196,0.000003446699,6.435124e-7,0.00174733,0.00006168576,0.01380038,0.00109601,0.000005464879,0.9800353],"study_design_scores_gemma":[0.0002279544,0.00004191631,0.06140061,0.00005835362,0.00001475706,0.00003491202,0.00135947,0.9133628,0.02033588,0.0008205213,0.001970063,0.0003727864],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3193874,0.0001051768,0.6799185,0.00009067058,0.00004924384,0.0002468872,0.000003967605,0.0001709412,0.00002719924],"genre_scores_gemma":[0.6878859,0.0000201749,0.3118109,0.00005176511,0.00004095906,0.000171131,0.000005272079,0.000005403492,0.000008439531],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9796625,"threshold_uncertainty_score":0.439938,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09000140225195971,"score_gpt":0.3105439723065407,"score_spread":0.220542570054581,"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."}}