{"id":"W2977404547","doi":"10.1159/000502915","title":"Personalised Nutrition Technologies and Innovations: A Cross-National Survey of Registered Dietitians","year":2019,"lang":"en","type":"article","venue":"Public Health Genomics","topic":"Nutrition, Genetics, and Disease","field":"Biochemistry, Genetics and Molecular Biology","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medicine; Family medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002059543,0.0001253284,0.0003650399,0.000778534,0.0006084139,0.0007890707,0.0003395984,0.000757621,0.001671719],"category_scores_gemma":[0.005522027,0.0004338858,0.0003690893,0.001326866,0.0003596317,0.000846306,0.0008410584,0.0007076761,0.0006092623],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005866202,"about_ca_system_score_gemma":0.0009386976,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01640955,"about_ca_topic_score_gemma":0.02155889,"domain_scores_codex":[0.9984547,0.0004596523,0.000234017,0.0001511576,0.0004972563,0.0002032287],"domain_scores_gemma":[0.9962615,0.0009493432,0.001507182,0.0002040647,0.000571563,0.0005061629],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004317398,0.000231518,0.9900539,0.00007093255,0.00002051921,0.0001016836,0.004702773,0.00001879205,0.0002249404,0.00001891822,0.0003353508,0.004177522],"study_design_scores_gemma":[0.000007243996,0.0002214914,0.9884384,0.00003251693,0.000009969267,0.0001900084,0.01014213,0.000103271,0.00005478079,0.000007569766,0.000786355,0.000006177373],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9989542,0.0000903969,0.00005094733,0.0001311841,0.000003657686,0.00004276336,0.0002229275,0.000002182684,0.0005016548],"genre_scores_gemma":[0.9982414,0.0003760116,0.000242622,0.0002679776,0.00000625052,0.0000996225,0.0002842242,0.000002590498,0.0004792696],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01640955,"threshold_uncertainty_score":0.03262806,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07182517109788114,"score_gpt":0.3349068044277544,"score_spread":0.2630816333298732,"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."}}