{"id":"W4400528792","doi":"10.1145/3626772.3657857","title":"MealRec <sup>+</sup> : A Meal Recommendation Dataset with Meal-Course Affiliation for Personalization and Healthiness","year":2024,"lang":"en","type":"article","venue":"","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Personalization; Meal; Computer science; Course (navigation); Recommender system; World Wide Web; Food science; Engineering; Chemistry","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":[0.0005876796,0.001575928,0.000919821,0.001776151,0.0007051522,0.0009046476,0.001995032,0.002316827,0.0116885],"category_scores_gemma":[0.002609845,0.0004211092,0.001289273,0.00263918,0.0002994273,0.0008736032,0.001180158,0.001369785,0.01243553],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009275971,"about_ca_system_score_gemma":0.0009598525,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04502098,"about_ca_topic_score_gemma":0.1444997,"domain_scores_codex":[0.9993532,0.0001206839,0.00008232724,0.0002278328,0.0001403549,0.00007554196],"domain_scores_gemma":[0.9989441,0.0002128937,0.00008680862,0.000294473,0.0002930087,0.0001686606],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001214065,0.000867967,0.02668419,0.002251104,0.0004143529,0.0003254797,0.0002640855,0.003873079,0.004066119,0.001130899,0.8959277,0.06298096],"study_design_scores_gemma":[0.001222342,0.0009291802,0.1422304,0.0006108119,0.0003505498,0.001213162,0.0009763204,0.03570923,0.008564285,0.002472031,0.8053309,0.0003909207],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0284396,0.0009125406,0.003223113,0.0004123743,0.0001998611,0.000227616,0.9589204,0.004074424,0.003590095],"genre_scores_gemma":[0.01649221,0.000221947,0.009954928,0.0001754219,0.00002641039,0.0002071903,0.9707345,0.0001229481,0.002064375],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.04502098,"threshold_uncertainty_score":0.08951783,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02703942984801776,"score_gpt":0.3063070756016166,"score_spread":0.2792676457535989,"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."}}