{"id":"W6968863970","doi":"10.5281/zenodo.4058838","title":"Silent Noise: Channel Noise in Visual Communications","year":2020,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Visual communication; Noise (video); Communication design; Graphics; Channel (broadcasting); Fidelity; Communications system; Terminology","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":[0.004962478,0.001265184,0.0007406372,0.002043463,0.00322447,0.01035191,0.002251041,0.003342784,0.009353867],"category_scores_gemma":[0.03337291,0.0007994838,0.0007362829,0.001794723,0.009536811,0.01285067,0.005588899,0.00341084,0.001815847],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001976762,"about_ca_system_score_gemma":0.001471526,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002249415,"about_ca_topic_score_gemma":0.001090943,"domain_scores_codex":[0.9904813,0.004814287,0.0004044692,0.001137555,0.002570016,0.0005923702],"domain_scores_gemma":[0.9690301,0.01988326,0.002164493,0.004979183,0.003292758,0.0006502618],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000482398,0.00007066866,0.003101394,0.0006787062,0.00005262227,0.00108907,0.02601986,0.008789646,0.008845524,0.8727149,0.00842145,0.06973381],"study_design_scores_gemma":[0.0001035342,0.0003451501,0.002700058,0.001352885,0.000189274,0.003695811,0.01482031,0.05269767,0.02390398,0.6973282,0.2025716,0.000291584],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04784616,0.001989519,0.8573802,0.003522095,0.0006968161,0.0002355091,0.0001699819,0.00143865,0.08672111],"genre_scores_gemma":[0.8597159,0.001582243,0.1103589,0.001696958,0.0005581416,0.0005760176,0.0002541617,0.001153457,0.02410413],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01035191,"threshold_uncertainty_score":0.03129184,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07334605655952856,"score_gpt":0.3039716357720551,"score_spread":0.2306255792125265,"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."}}