{"id":"W2574770385","doi":"10.5594/m001698","title":"Flexible SDI - The Universal Transport for Streamed Media","year":2016,"lang":"en","type":"article","venue":"","topic":"Multimedia Communication and Technology","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Semtech (Canada)","funders":"","keywords":"Computer science; High-definition television; Flexibility (engineering); Layer (electronics); Digital television; Multimedia; Operating system; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001555032,0.0005244141,0.0003613673,0.001425491,0.001156159,0.002831039,0.001049827,0.0006720386,0.004396012],"category_scores_gemma":[0.002468975,0.0003421789,0.0004370654,0.001489791,0.001285568,0.002952319,0.003516591,0.001470356,0.002070485],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001392493,"about_ca_system_score_gemma":0.001545333,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002889761,"about_ca_topic_score_gemma":0.001374208,"domain_scores_codex":[0.9991012,0.000120847,0.00007395798,0.0001585827,0.0003654908,0.0001799452],"domain_scores_gemma":[0.998853,0.0001413134,0.00007568076,0.0003902217,0.0004084558,0.0001313768],"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":[0.0003594725,0.0001315608,0.004819837,0.0003524306,0.00004609584,0.000489036,0.001688398,0.005831508,0.03961742,0.3812622,0.04460892,0.520793],"study_design_scores_gemma":[0.00009659124,0.000283363,0.002537363,0.0003965936,0.00005860287,0.00118782,0.0008052971,0.05066759,0.0880809,0.08817513,0.7675404,0.0001704594],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.06034118,0.00419105,0.764698,0.001978209,0.001741183,0.0006397246,0.002204631,0.01205725,0.1521488],"genre_scores_gemma":[0.7067385,0.004201435,0.223083,0.0009494468,0.0005212084,0.0006023751,0.004117196,0.001259864,0.05852712],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.004396012,"threshold_uncertainty_score":0.01470613,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04833148077985398,"score_gpt":0.3271587477627799,"score_spread":0.2788272669829259,"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."}}