{"id":"W3008978453","doi":"10.1038/s41597-020-0397-7","title":"Tesco Grocery 1.0, a large-scale dataset of grocery purchases in London","year":2020,"lang":"en","type":"article","venue":"Scientific Data","topic":"Nutritional Studies and Diet","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bell (Canada)","funders":"","keywords":"Representativeness heuristic; Census; Scale (ratio); Grocery store; Geography; Business; Population; Marketing; Statistics; Environmental health; Medicine; Cartography; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004810493,0.00009729184,0.0002601487,0.00008680221,0.0000933685,0.0000355311,0.0004601782,0.00003228165,0.0003041753],"category_scores_gemma":[0.0004142891,0.00008332809,0.00003062791,0.0006606969,0.0002002384,0.0002416051,0.0009569062,0.0001114352,0.0001079247],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001468463,"about_ca_system_score_gemma":0.00008034464,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005827017,"about_ca_topic_score_gemma":0.0001582322,"domain_scores_codex":[0.9984279,0.00001652124,0.000307498,0.0005934925,0.0004032712,0.0002513011],"domain_scores_gemma":[0.9988139,0.00005124711,0.00006772928,0.0008534992,0.000066796,0.0001468202],"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":[0.0001493631,0.0004415186,0.00857562,0.0003011464,0.00001690231,0.00004586049,0.0001034625,8.242587e-7,0.002757678,0.00005886951,0.9869753,0.0005734788],"study_design_scores_gemma":[0.001912698,0.0001285374,0.009280523,0.0001675444,0.00005089214,0.00001131313,0.0008275154,0.0009725525,0.001327875,0.0001650836,0.9850287,0.0001267918],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.3601759,0.008981965,0.0005744469,0.02275778,0.001327442,0.001236211,0.6024172,0.0001204248,0.002408624],"genre_scores_gemma":[0.6395639,0.0004113491,0.004558894,0.00414772,0.0005463004,0.00002142818,0.3501446,0.00003610134,0.0005697592],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.279388,"threshold_uncertainty_score":0.3398021,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0809298758706811,"score_gpt":0.3203160546477765,"score_spread":0.2393861787770954,"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."}}