{"id":"W4413108642","doi":"10.1016/j.ajcnut.2025.08.001","title":"Structural funding bias in red meat research: the elephant in the room","year":2025,"lang":"en","type":"letter","venue":"American Journal of Clinical Nutrition","topic":"Agriculture Sustainability and Environmental Impact","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"St. Michael's Hospital","funders":"Instituto de Salud Carlos III; Canadian Institutes of Health Research; European Commission; Institute for the Advancement of Food and Nutrition Sciences; National Honey Board; Diabetes Canada; U.S. Department of Agriculture","keywords":"Business; Red meat; Food science; Biology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.02836194,0.0005107095,0.001741009,0.0008949349,0.008060725,0.007313277,0.002735943,0.08062645,0.007332254],"category_scores_gemma":[0.09237897,0.00077219,0.001113818,0.00122697,0.01033499,0.00563167,0.003342986,0.04812327,0.00256821],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006611142,"about_ca_system_score_gemma":0.02203829,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01025383,"about_ca_topic_score_gemma":0.02036846,"domain_scores_codex":[0.9827208,0.007942805,0.001514002,0.001857078,0.00380185,0.002163423],"domain_scores_gemma":[0.9103962,0.05933322,0.004294032,0.002343181,0.007016995,0.01661643],"domain_codex":null,"domain_gemma":"incentives","domain_candidate":"incentives","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001710292,0.0000675488,0.004436375,0.0001107408,0.00007034005,0.002989712,0.001063224,0.0000667789,0.0003494432,0.01768034,0.9562464,0.0167481],"study_design_scores_gemma":[0.0005627764,0.0001943233,0.005751531,0.001439574,0.0001495195,0.004092338,0.004742898,0.0008187286,0.0005274291,0.07247489,0.9090898,0.0001561726],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.0005895149,0.0006398767,0.0000477574,0.9926568,0.004600945,0.000003983457,0.00001004828,0.000004043973,0.001447055],"genre_scores_gemma":[0.007995807,0.0007022463,0.0001722928,0.9640551,0.02445989,0.00002340204,0.000008915451,0.00001367814,0.002568682],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.9716381,"threshold_uncertainty_score":0.149994,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1640137858510266,"score_gpt":0.4232498385334111,"score_spread":0.2592360526823845,"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."}}