{"id":"W2895552632","doi":"10.1145/3209280.3209524","title":"A Market Analytics Approach to Restaurant Review Data","year":2018,"lang":"en","type":"article","venue":"","topic":"Digital Marketing and Social Media","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Market research; Computer science; Identification (biology); Data science; Analytics; Social media analytics; Data extraction; Social media; Consumer behaviour; Data mining; Marketing; Business; World Wide Web","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":[0.003763584,0.0008861751,0.0009825662,0.0145448,0.0007679778,0.002832548,0.001099285,0.0008449809,0.0025895],"category_scores_gemma":[0.01659184,0.0003878647,0.001222291,0.01114288,0.0002905052,0.002541272,0.001220861,0.001120313,0.002128719],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009140988,"about_ca_system_score_gemma":0.00160683,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006631525,"about_ca_topic_score_gemma":0.01212332,"domain_scores_codex":[0.9957137,0.001246682,0.0006193753,0.0007517133,0.001489528,0.0001789908],"domain_scores_gemma":[0.9881434,0.00564806,0.00166791,0.001259705,0.003021566,0.0002594154],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0005007802,0.00102488,0.0644388,0.002298916,0.0004919347,0.001614535,0.002922594,0.01169886,0.03439295,0.0176736,0.04154706,0.8213952],"study_design_scores_gemma":[0.0001476757,0.0008843517,0.1080635,0.0003591294,0.0002980043,0.001715042,0.004585671,0.6099805,0.03220471,0.03232543,0.2091374,0.0002987522],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1857828,0.002619865,0.7136584,0.003889076,0.0005065702,0.006182055,0.06293131,0.01069317,0.01373668],"genre_scores_gemma":[0.2657633,0.0008048047,0.6932153,0.0002694966,0.0005025002,0.003272216,0.03184546,0.0003433442,0.003983553],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0145448,"threshold_uncertainty_score":0.01990396,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1190047511621405,"score_gpt":0.3815238264598335,"score_spread":0.2625190752976929,"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."}}