{"id":"W4255510155","doi":"10.32920/ryerson.14652366","title":"Palate: The App for Finding Restaurant Faster","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Digital Marketing and Social Media","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Reservation; Process (computing); Marketing; Computer science; Moment (physics); App store; Interface (matter); Advertising; 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":[0.0005075168,0.0008619698,0.0004360138,0.0006192792,0.0004059366,0.001113842,0.000975106,0.0007519047,0.02512338],"category_scores_gemma":[0.00195613,0.0003157823,0.0004604088,0.0003857194,0.0002726236,0.00279565,0.001582594,0.0007967235,0.006711673],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001150684,"about_ca_system_score_gemma":0.0003437839,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003752793,"about_ca_topic_score_gemma":0.0008095203,"domain_scores_codex":[0.999763,0.0000559448,0.00001655889,0.00005188393,0.0000852344,0.00002749801],"domain_scores_gemma":[0.9992427,0.000357631,0.00004660081,0.00009215484,0.0001391693,0.0001218706],"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":[0.00203151,0.001031473,0.01177885,0.003099616,0.000117003,0.001411701,0.008189111,0.0005297056,0.07689741,0.01744598,0.1361527,0.7413149],"study_design_scores_gemma":[0.0004581385,0.005324549,0.06374802,0.0008048828,0.0005634796,0.007045813,0.00621514,0.02135988,0.04517642,0.01534406,0.8335648,0.0003948433],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.3744702,0.003411652,0.3376595,0.004429121,0.001621894,0.004591746,0.007094594,0.0753444,0.191377],"genre_scores_gemma":[0.476519,0.002448241,0.3571228,0.002391278,0.0004314787,0.002489166,0.004916481,0.003824315,0.1498572],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02512338,"threshold_uncertainty_score":0.08404613,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05396543135133627,"score_gpt":0.3410569671477249,"score_spread":0.2870915357963887,"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."}}