{"id":"W4376472551","doi":"10.1007/978-3-031-24663-0_21","title":"Food Labels: Sorting the Wheat from the Chaff","year":2023,"lang":"en","type":"book-chapter","venue":"Nutrition and health","topic":"Consumer Attitudes and Food Labeling","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Athabasca University","funders":"","keywords":"Sorting; Chaff; Selection (genetic algorithm); Marketing; Nutrition facts label; Reinterpretation; Food choice; Computer science; Advertising; Biotechnology; Business; Food science; Artificial intelligence; Medicine; Biology; Botany","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003734776,0.0001699524,0.0003391935,0.00004118559,0.0003919392,0.00003934969,0.00007135379,0.0001428744,0.0001421279],"category_scores_gemma":[0.00001601406,0.0001001645,0.00009412471,0.00003135689,0.00006642145,0.00001674275,0.00005246144,0.0005582385,0.00006241287],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004954221,"about_ca_system_score_gemma":0.0001155149,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002703478,"about_ca_topic_score_gemma":0.001189018,"domain_scores_codex":[0.9989625,0.00001950038,0.0003304514,0.0002525718,0.0002257861,0.0002091486],"domain_scores_gemma":[0.9992338,0.0001647908,0.000149158,0.0002775627,0.00005757736,0.0001170551],"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":[0.0003277089,0.000278523,0.001709839,0.004230891,0.001988119,0.00004721812,0.004359576,2.875815e-7,0.00006661133,0.4727201,0.1116515,0.4026197],"study_design_scores_gemma":[0.002634266,0.0008627158,0.004892269,0.006412786,0.0005127909,0.00004689889,0.0004647085,0.00007814728,0.000004771775,0.03082927,0.9529744,0.0002869286],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"review","genre_scores_codex":[0.001748527,0.3300061,0.00005573006,0.5580672,0.001248756,0.004068314,0.0007069996,0.0005375862,0.1035608],"genre_scores_gemma":[0.3072145,0.3418426,0.0009823859,0.1025507,0.01013767,0.0003139321,0.002299292,0.0005432316,0.2341157],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.841323,"threshold_uncertainty_score":0.4084589,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1266077724328483,"score_gpt":0.3388476376713039,"score_spread":0.2122398652384556,"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."}}