{"id":"W6944965861","doi":"10.21427/xca2-8y93","title":"Food History as an Ingredient in Teaching Early Modern Mobility","year":2022,"lang":"en","type":"article","venue":"Arrow - TU Dublin (Technological University Dublin)","topic":"Mathematics, Computing, and Information Processing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Ingredient; Food processing; Social history (medicine); Consumption (sociology); Product (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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00247749,0.0004459148,0.0002708391,0.0009524368,0.00364682,0.003796354,0.0009563359,0.00133147,0.009473467],"category_scores_gemma":[0.003281997,0.0003790507,0.0002848404,0.0008154647,0.008922677,0.007602376,0.005216235,0.002893208,0.00114205],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00375307,"about_ca_system_score_gemma":0.001731938,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001381227,"about_ca_topic_score_gemma":0.004449108,"domain_scores_codex":[0.9990263,0.0006143741,0.00002546672,0.000090398,0.0001234048,0.0001200852],"domain_scores_gemma":[0.9978217,0.001557987,0.00009313118,0.00009762651,0.0001070946,0.0003225612],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007409348,0.0001916277,0.002952875,0.0005680606,0.00000805025,0.0005679431,0.1706994,0.0008586044,0.001709434,0.6690682,0.02568742,0.1276142],"study_design_scores_gemma":[0.00002219761,0.0001113761,0.001648726,0.0005798605,0.00001069672,0.0003446764,0.06086666,0.0005834963,0.001436568,0.1963898,0.7379804,0.00002561663],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2124541,0.01462812,0.08185712,0.1221158,0.003930485,0.0001769269,0.00008174042,0.0003896238,0.564366],"genre_scores_gemma":[0.9150096,0.007753995,0.02677284,0.003125334,0.0005159543,0.0001282701,0.00004898888,0.0001318384,0.04651323],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009473467,"threshold_uncertainty_score":0.03169191,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02425703375681046,"score_gpt":0.2077400480008342,"score_spread":0.1834830142440237,"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."}}