{"id":"W4301395463","doi":"10.1145/3565482","title":"Design and Evaluation of Technologies for Informed Food Choices","year":2022,"lang":"en","type":"article","venue":"ACM Transactions on Computer-Human Interaction","topic":"Innovative Human-Technology Interaction","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; University of Waterloo","keywords":"Heuristics; Summative assessment; Formative assessment; Process (computing); Food choice; Literacy; Computer science; Knowledge management; Work (physics); Psychology; Management science; Medicine; Engineering; Mathematics education; Pedagogy","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0008600182,0.0002199533,0.0002389249,0.00111977,0.0008463805,0.00009949513,0.0009262508,0.0001061182,0.00005280358],"category_scores_gemma":[0.00006710249,0.0002427815,0.00009281669,0.0006090525,0.0001000485,0.00116187,0.0001047368,0.0005162921,0.000003251264],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004646548,"about_ca_system_score_gemma":0.00009270268,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001286993,"about_ca_topic_score_gemma":0.00002208863,"domain_scores_codex":[0.9980445,0.0002144341,0.0005129189,0.0005005223,0.0004925429,0.0002350796],"domain_scores_gemma":[0.9975966,0.0006623869,0.000444749,0.0007715496,0.0005041969,0.00002049298],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002093563,0.0007016602,0.00002292792,0.00007822031,0.0003542656,0.000001111923,0.001812012,0.07255021,0.01207843,0.01868289,0.0006511763,0.8928577],"study_design_scores_gemma":[0.00296162,0.008272176,0.0004019285,0.0001060749,0.0001362514,0.0001739134,0.001263888,0.7634309,0.1631168,0.05393266,0.00560968,0.0005940979],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1156462,0.00002436291,0.8807887,0.0006864074,0.001217508,0.001046657,0.0000099853,0.0005143282,0.00006583599],"genre_scores_gemma":[0.9031242,0.00000600231,0.09569921,0.00007196251,0.00002567562,0.001014216,0.00001301969,0.00001603583,0.00002965277],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8922637,"threshold_uncertainty_score":0.9900342,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09149992634089794,"score_gpt":0.3527036482746584,"score_spread":0.2612037219337605,"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."}}