{"id":"W4412835399","doi":"10.1021/acsomega.4c10748","title":"Nutritional Supplementation Benefits in <i>Caenorhabditis elegans</i> under Developmental Disruption and Stress Conditions","year":2025,"lang":"en","type":"article","venue":"ACS Omega","topic":"Genetics, Aging, and Longevity in Model Organisms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"IONICS Mass Spectrometry (Canada)","funders":"National Institutes of Health; Universidade Federal de Pernambuco; Fundação de Amparo à Ciência e Tecnologia do Estado de Pernambuco; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; Universidade de Pernambuco; Fundação de Amparo à Pesquisa do Estado de São Paulo","keywords":"Caenorhabditis elegans; Biology; Genetics; Gene","routes":{"ca_aff":true,"ca_fund":false,"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":[],"consensus_categories":[],"category_scores_codex":[0.00009310677,0.0004946475,0.0003513041,0.0003220236,0.0003384026,0.0003043755,0.0003459601,0.000394842,0.0025334],"category_scores_gemma":[0.0001047745,0.0002045169,0.0005930982,0.000153457,0.0001493726,0.0002879968,0.0002274047,0.0004629463,0.0006363037],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000323254,"about_ca_system_score_gemma":0.000327412,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005232434,"about_ca_topic_score_gemma":0.008644982,"domain_scores_codex":[0.9999381,0.000003763027,0.000005620557,0.00002347216,0.00001833797,0.00001072959],"domain_scores_gemma":[0.999947,0.000005841531,0.00001724485,0.000004541533,0.00001129564,0.00001409134],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004364376,0.00009347453,0.001458469,0.0004440175,0.00005002291,0.0001332177,0.00001622136,0.001697229,0.9877061,0.0002659055,0.001215178,0.006483597],"study_design_scores_gemma":[0.0001551196,0.001283285,0.04353151,0.0001719505,0.0003435487,0.0004159648,0.0001202814,0.03719603,0.8909512,0.0007836164,0.02494499,0.0001023926],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9720695,0.001688739,0.00645827,0.0003159968,0.00010443,0.00008181461,0.01190212,0.002258542,0.00512045],"genre_scores_gemma":[0.9602901,0.002241565,0.0187676,0.0002344986,0.00001331989,0.0001459182,0.0115077,0.0004463781,0.006352937],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005232434,"threshold_uncertainty_score":0.01040393,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008639119248608216,"score_gpt":0.2538685291875445,"score_spread":0.2452294099389363,"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."}}