{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007239557,0.0001610279,0.0001685057,0.0001323009,0.000166673,0.0004526207,0.0001994567,0.00007221264,0.0000225795],"category_scores_gemma":[0.00001321875,0.0001210027,0.0000275266,0.0003237675,0.00001738901,0.001178514,0.00006504124,0.00008248483,0.000004759118],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007381956,"about_ca_system_score_gemma":0.0001133114,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004091778,"about_ca_topic_score_gemma":0.0002742026,"domain_scores_codex":[0.9987571,0.00008166732,0.0002614043,0.0005007382,0.0001872263,0.0002119222],"domain_scores_gemma":[0.9993351,0.0001309731,0.00007075721,0.0002680415,0.0001069278,0.00008818398],"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":[0.00004893419,0.0001311493,0.0005295999,0.00114319,0.0001230217,0.000006123717,0.00720948,0.00008622665,0.00005343868,0.3059086,0.3072995,0.3774607],"study_design_scores_gemma":[0.0004048281,0.0003096414,0.0001593038,0.0001346523,0.00002536795,0.00006127806,0.0002648861,0.8773832,0.000266842,0.004050938,0.1166855,0.0002534768],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0006684714,0.0001189329,0.9822478,0.01492225,0.0001752842,0.000694998,0.0001745772,0.0005007873,0.0004969009],"genre_scores_gemma":[0.7490026,0.0001896854,0.2419268,0.002299615,0.0003799719,0.0006420539,0.004710014,0.00006132382,0.0007879167],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.877297,"threshold_uncertainty_score":0.4934346,"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."}}