{"id":"W3184661901","doi":"10.82308/44888","title":"An analysis of complementary products associated with unhealthy food purchases using household grocery sales data in Montréal, Canada","year":2019,"lang":"en","type":"article","venue":"eScholarship@McGill (McGill)","topic":"Food Waste Reduction and Sustainability","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Business; Marketing","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009128081,0.0002670031,0.0005792283,0.0001049691,0.0003557154,0.00003245154,0.0006480733,0.0001006143,0.00005731201],"category_scores_gemma":[0.0002662997,0.0001360253,0.00006624028,0.002335726,0.0000728652,0.000697233,0.0002131553,0.0002940915,5.268747e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007348568,"about_ca_system_score_gemma":0.0001028417,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5396762,"about_ca_topic_score_gemma":0.9405327,"domain_scores_codex":[0.996987,0.0004646515,0.0005688854,0.0008587547,0.0006040148,0.0005166287],"domain_scores_gemma":[0.9985394,0.0002099804,0.0003240065,0.0004732372,0.000250695,0.000202708],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001423165,0.005111455,0.5623006,0.0005587023,0.002818978,0.0001036404,0.00003965664,0.02247374,0.2954379,0.004705974,0.00003500184,0.1049911],"study_design_scores_gemma":[0.001451462,0.002466141,0.9583786,0.0001541204,0.0007383365,0.00001551727,0.01660818,0.002849936,0.01016718,0.000465613,0.005428329,0.001276595],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9931589,0.0001421109,1.632573e-8,0.0001944251,0.00008850409,0.0005135462,0.005775856,0.00005319292,0.00007347536],"genre_scores_gemma":[0.9979439,0.0000221765,0.00007315652,0.0001993664,0.00001463188,0.000006421556,0.001716783,0.00000522658,0.0000183521],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4008565,"threshold_uncertainty_score":0.554695,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05071451638958966,"score_gpt":0.2362768591411559,"score_spread":0.1855623427515662,"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."}}