{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006567537,0.00009821852,0.0001454635,0.0001126664,0.000079923,0.00004494885,0.0001305486,0.0001264943,0.000009937246],"category_scores_gemma":[0.0004186528,0.0001114271,0.0000319122,0.000177909,0.0001480154,0.000008962566,0.00006924615,0.00005629187,0.000002821695],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005234025,"about_ca_system_score_gemma":0.0006709076,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008428749,"about_ca_topic_score_gemma":0.00009795281,"domain_scores_codex":[0.9989734,0.00006965911,0.0003239634,0.000282431,0.0001332214,0.0002173738],"domain_scores_gemma":[0.9988599,0.00002189424,0.0001832476,0.0002418649,0.0006144301,0.00007862461],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006264193,0.001600049,0.8880129,0.002453024,0.0001854957,9.261695e-7,0.0005708731,0.00003330535,0.06296273,0.00788845,0.01945656,0.01620922],"study_design_scores_gemma":[0.004540065,0.000753134,0.840799,0.00005624028,0.000006412851,0.00001812993,0.001133531,0.0002848647,0.003547887,0.002216388,0.1461686,0.0004756757],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9914027,0.003406272,0.0004832258,0.003204947,0.0001046822,0.0004114727,0.0007286228,0.00002286237,0.0002351906],"genre_scores_gemma":[0.9941221,0.002286454,0.001157845,0.0006844704,0.00005645504,0.00003806076,0.001516079,0.00001439481,0.00012418],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1267121,"threshold_uncertainty_score":0.4543864,"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."}}