{"id":"W2221637152","doi":"10.1016/j.jneb.2015.04.324","title":"A Picture Is Worth a Thousand Words: Customizing MyPlate for Low-Literate, Low-Income Families in 4 Steps","year":2015,"lang":"en","type":"article","venue":"Journal of Nutrition Education and Behavior","topic":"Child Development and Digital Technology","field":"Social Sciences","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Low income; Visual arts; Gerontology; Art; Psychology; Sociology; Medicine; Socioeconomics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003711843,0.00008071914,0.0001723578,0.0003610552,0.0001025006,0.0001408636,0.00009593144,0.0001128469,0.0000148416],"category_scores_gemma":[0.0001076941,0.00007218913,0.00005059229,0.0002972161,0.00007184288,0.0004815382,0.00001228477,0.0001298507,0.00000186418],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001268909,"about_ca_system_score_gemma":0.0004020034,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001840678,"about_ca_topic_score_gemma":0.0001138829,"domain_scores_codex":[0.9991997,0.00003443566,0.0003387162,0.0001011081,0.0001801723,0.0001458172],"domain_scores_gemma":[0.9992845,0.00004615271,0.0001996313,0.00005049601,0.0002975092,0.0001217263],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006442741,0.01761378,0.4636779,0.0003786328,0.0000497962,0.00004215959,0.1601365,0.000002449168,0.0009066394,0.005848514,0.03106145,0.3196379],"study_design_scores_gemma":[0.01404775,0.0007698626,0.2680367,0.002902432,0.0002038708,0.000225126,0.3108476,0.00001278648,0.001985697,0.03031029,0.369621,0.001036905],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9959254,0.0006345613,0.00003841677,0.001711832,0.0006573003,0.0003375107,0.000007136735,0.00001573999,0.0006721015],"genre_scores_gemma":[0.9968161,0.0003502298,0.001652224,0.000268961,0.0002882511,0.00005938347,0.000006823818,0.000006390062,0.0005516261],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3385596,"threshold_uncertainty_score":0.2943788,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0224269406511851,"score_gpt":0.3264795920423557,"score_spread":0.3040526513911705,"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."}}