{"id":"W7161987460","doi":"10.82308/41837","title":"Advancing the science of precision retailing through digital innovation in traditional and modern agri-food markets","year":2024,"lang":"en","type":"dissertation","venue":"","topic":"Consumer Retail Behavior Studies","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Context (archaeology); Technology transfer; Digital transformation","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":[0.003777182,0.0004376956,0.0005107396,0.002439431,0.001758543,0.01196935,0.001175465,0.002416358,0.01063265],"category_scores_gemma":[0.008246285,0.0003360544,0.0008734809,0.003175638,0.01126067,0.01508744,0.004046982,0.002214099,0.001102943],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00460113,"about_ca_system_score_gemma":0.003609124,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002950787,"about_ca_topic_score_gemma":0.003482274,"domain_scores_codex":[0.9977726,0.0008498335,0.0001143717,0.0003708776,0.0007295492,0.000162615],"domain_scores_gemma":[0.9900506,0.007185899,0.0006146317,0.001270265,0.0006612316,0.0002172596],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00003399334,0.00003929605,0.001892676,0.0004112712,0.00001520788,0.000126672,0.005182516,0.001232345,0.0008024346,0.9113877,0.001010657,0.07786503],"study_design_scores_gemma":[0.0000266793,0.0001323517,0.006101469,0.001442578,0.00004696929,0.0004270781,0.007805547,0.005915958,0.003332479,0.8006421,0.1740661,0.00006057595],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1926752,0.02512286,0.2108256,0.02713545,0.0007309998,0.0002310529,0.0002355753,0.0002906198,0.5427527],"genre_scores_gemma":[0.8721662,0.02244386,0.07025313,0.001511386,0.0004357899,0.0002363988,0.00009950575,0.0000894626,0.03276427],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01196935,"threshold_uncertainty_score":0.03556979,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03511349879293486,"score_gpt":0.2694677283712484,"score_spread":0.2343542295783136,"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."}}