{"id":"W7044138098","doi":"","title":"Using Loyalty Points to Encourage Healthy Food Choices in Online Shopping","year":2022,"lang":"en","type":"dissertation","venue":"The Atrium (University of Guelph)","topic":"Consumer Attitudes and Food Labeling","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Loyalty; Brand loyalty; Healthy food; Food products; Work (physics); Logit; Test (biology)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004200245,0.0003487439,0.0004622518,0.0006466207,0.000778938,0.001392989,0.000500729,0.0007145399,0.002887557],"category_scores_gemma":[0.01436327,0.0003176105,0.0004242524,0.0004657546,0.0006144998,0.0008043028,0.0007564314,0.001025617,0.0004563301],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008037714,"about_ca_system_score_gemma":0.00103785,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01158661,"about_ca_topic_score_gemma":0.01658398,"domain_scores_codex":[0.9972723,0.001643121,0.00008459477,0.0001617048,0.0006107363,0.0002274469],"domain_scores_gemma":[0.9828744,0.01258412,0.001661496,0.0008603836,0.0007933927,0.001226305],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.006008939,0.05673253,0.5025175,0.0005610305,0.0004447069,0.0001437898,0.008025733,0.005058051,0.01654026,0.002826845,0.002212497,0.3989282],"study_design_scores_gemma":[0.001534289,0.03945924,0.8819128,0.0002402159,0.0007603696,0.0001406326,0.006378664,0.04906076,0.01051323,0.003479894,0.006295375,0.0002244082],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9967892,0.00001773494,0.0003879569,0.0001209208,0.000004599059,0.00006042257,0.00001849178,0.00001787195,0.002582741],"genre_scores_gemma":[0.9957508,0.00004254451,0.002875402,0.0001138595,0.000006254249,0.00007788622,0.00004829079,0.000006552284,0.001078368],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01158661,"threshold_uncertainty_score":0.02303833,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04472655283039486,"score_gpt":0.307702610692321,"score_spread":0.2629760578619262,"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."}}