{"id":"W2331160648","doi":"10.1109/ccnc.2014.6994395","title":"A semantic social networking service using smart TV","year":2014,"lang":"en","type":"article","venue":"","topic":"Multimedia Communication and Technology","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Synchronizing; Encryption; Key (lock); Broadcasting (networking); Service (business); IPTV; Cloud computing; Object (grammar); Cryptography; Computer security; World Wide Web; Internet privacy; Multimedia; Telecommunications; Artificial intelligence","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":[0.0007455748,0.0004660844,0.0004620403,0.001008091,0.0009758845,0.001383611,0.001085449,0.00119942,0.006143444],"category_scores_gemma":[0.001011122,0.0002074042,0.0004219542,0.0007915644,0.0004359664,0.003098022,0.002360104,0.0008006152,0.0025777],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005859754,"about_ca_system_score_gemma":0.0007684914,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002985117,"about_ca_topic_score_gemma":0.001929719,"domain_scores_codex":[0.9993079,0.0001457252,0.00006088394,0.00009916993,0.0002773476,0.0001089763],"domain_scores_gemma":[0.9994844,0.00008214087,0.00004362161,0.0001143362,0.0001316677,0.0001438481],"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":[0.001506213,0.0007828951,0.005535871,0.000805473,0.000164293,0.002033652,0.001291247,0.008989202,0.07915999,0.1885892,0.1289054,0.5822365],"study_design_scores_gemma":[0.0002635044,0.0005389747,0.003944611,0.0001288706,0.0001521844,0.002333613,0.0009003195,0.33477,0.03997789,0.04970375,0.5670574,0.0002288375],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06431139,0.001359142,0.7938697,0.002627398,0.001227028,0.001007263,0.001872642,0.03095983,0.1027656],"genre_scores_gemma":[0.7797671,0.00106916,0.1657954,0.001526821,0.000569127,0.0007401109,0.004341833,0.0005822453,0.04560817],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006143444,"threshold_uncertainty_score":0.02055186,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08013172677277867,"score_gpt":0.3567996097161223,"score_spread":0.2766678829433436,"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."}}