{"id":"W2750791552","doi":"10.1017/s1368980017001999","title":"Applying a food processing-based classification system to a food guide: a qualitative analysis of the Brazilian experience","year":2017,"lang":"en","type":"article","venue":"Public Health Nutrition","topic":"Consumer Attitudes and Food Labeling","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Thematic analysis; Food security; Government (linguistics); Civil society; Food industry; Population; Public relations; Qualitative research; Marketing; Food systems; Business; Political science; Sociology; Medicine; Environmental health; Social science; Geography; Agriculture; Politics","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":[0.001204291,0.0001185048,0.0004108144,0.0003331438,0.0006732515,0.0001237021,0.0002523974,0.0000640272,0.000006296522],"category_scores_gemma":[0.0006330953,0.00009355412,0.0001472415,0.0009124132,0.00008703657,0.000176574,0.00004317184,0.0001222368,0.000001626438],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003449726,"about_ca_system_score_gemma":0.0005942066,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002243345,"about_ca_topic_score_gemma":0.0004907203,"domain_scores_codex":[0.9981578,0.0001801105,0.0005927664,0.0003261752,0.0004399975,0.0003031688],"domain_scores_gemma":[0.9978636,0.00007082805,0.0005935525,0.0007041519,0.0005071419,0.0002607593],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0008705271,0.006338916,0.1324596,0.04009143,0.0049454,0.000003568364,0.2136947,0.00006317076,0.009343028,0.03607906,0.001383173,0.5547275],"study_design_scores_gemma":[0.01063182,0.00463693,0.5861878,0.01076098,0.002786515,0.00002464306,0.1804282,0.1354106,0.001756582,0.0001101919,0.0662178,0.001047884],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8451381,0.002478701,0.04151545,0.1031417,0.0002244387,0.006143761,0.0001824574,0.0001933657,0.0009819815],"genre_scores_gemma":[0.9953119,0.000007207804,0.002058787,0.0009245772,0.00004386239,0.001595303,0.00003639202,0.00001249711,0.000009467585],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5536796,"threshold_uncertainty_score":0.5178174,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1567165467969746,"score_gpt":0.4354386114052033,"score_spread":0.2787220646082288,"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."}}