{"id":"W2798934669","doi":"10.1145/3209978.3210140","title":"What Do Viewers Say to Their TVs?","year":2018,"lang":"en","type":"article","venue":"","topic":"Topic Modeling","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Domain (mathematical analysis); Taxonomy (biology); Information retrieval; Entertainment; Service (business); World Wide Web; Product (mathematics)","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":[0.0006999146,0.0002902176,0.0002551871,0.0009319289,0.0003969733,0.001498018,0.0002370774,0.0004792495,0.003411213],"category_scores_gemma":[0.005332145,0.0001067736,0.0002652867,0.0009833706,0.0003441571,0.001810134,0.000389979,0.0005300498,0.001121511],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004677278,"about_ca_system_score_gemma":0.0002841111,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01011656,"about_ca_topic_score_gemma":0.01019587,"domain_scores_codex":[0.9995524,0.0001587562,0.00002815771,0.0001031317,0.00008770512,0.00006979969],"domain_scores_gemma":[0.9971018,0.001985579,0.0003069339,0.00013101,0.0003361071,0.0001384859],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001612119,0.000313612,0.5107556,0.001108872,0.0001925767,0.0009735862,0.04075262,0.004907603,0.03293324,0.03947546,0.07603887,0.2909359],"study_design_scores_gemma":[0.00007788621,0.0005762242,0.5285301,0.000431161,0.0004089914,0.003006543,0.05967087,0.07536945,0.02465437,0.03981067,0.2672201,0.0002435113],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8769061,0.003012562,0.0495731,0.004899141,0.000243846,0.000169524,0.01737843,0.001471884,0.04634545],"genre_scores_gemma":[0.9850696,0.0007224114,0.005073549,0.0003622,0.0001534059,0.00003723487,0.00399428,0.000116544,0.004470906],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01011656,"threshold_uncertainty_score":0.02011532,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02807425847785326,"score_gpt":0.2655299071258418,"score_spread":0.2374556486479886,"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."}}