{"id":"W4399387582","doi":"10.1186/s40795-024-00889-z","title":"Knowledge mobilization between the food industry and public health nutrition scientists: findings from a case study","year":2024,"lang":"en","type":"article","venue":"BMC Nutrition","topic":"Global Public Health Policies and Epidemiology","field":"Business, Management and Accounting","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"Canadian Nutrition Society","keywords":"Thematic analysis; Context (archaeology); Public health; Food industry; Medicine; Product (mathematics); Public relations; Quality (philosophy); Marketing; Qualitative research; Population health; Population; Environmental health; Medical education; Business; Food science; Sociology; Political science; Nursing; Social science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001626688,0.0001601395,0.0002428643,0.0003521496,0.0006488878,0.0008039926,0.0001364724,0.000180071,0.00003638291],"category_scores_gemma":[0.0002975356,0.0001288433,0.00005025524,0.001128876,0.00009377215,0.00103551,0.0001486165,0.0003358038,0.00005406045],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001411502,"about_ca_system_score_gemma":0.00009231761,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008502551,"about_ca_topic_score_gemma":0.002007831,"domain_scores_codex":[0.9983546,0.0001531242,0.0004596852,0.0004197705,0.0001584377,0.0004543483],"domain_scores_gemma":[0.9992128,0.0002847518,0.0001143687,0.0001968095,0.0001324489,0.00005882324],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002686641,0.003079777,0.3115679,0.006761028,0.0001478815,0.0000856124,0.001818481,0.00001227575,0.00001832747,0.03820914,0.6193604,0.01891229],"study_design_scores_gemma":[0.002012573,0.0002484303,0.04726468,0.0005353264,0.00008412325,0.0001115188,0.02520589,0.009219087,0.000001589376,0.01010966,0.9048596,0.0003475008],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9693331,0.002450378,0.0009202575,0.02483932,0.0005887053,0.001385922,0.00006351583,0.000208757,0.000210041],"genre_scores_gemma":[0.9950211,0.00006672671,0.00007589738,0.001853583,0.002458211,0.0002515932,0.0002407489,0.00001874174,0.00001337661],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2854992,"threshold_uncertainty_score":0.9980999,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1247881781886894,"score_gpt":0.3609437246145893,"score_spread":0.2361555464258999,"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."}}