{"id":"W4394841248","doi":"10.1371/journal.pone.0287864","title":"Investigating the potential of Juglans regia phytoconstituents for the treatment of cervical cancer utilizing network biology and molecular docking approach","year":2024,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Nuts composition and effects","field":"Nursing","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Department of Biotechnology, Ministry of Science and Technology, India; King Khalid University; Jawaharlal Nehru University","keywords":"Juglans; In silico; Docking (animal); Computational biology; Biology; Gene; DNA microarray; Microarray; Bioinformatics; Traditional medicine; Genetics; Gene expression; Botany; Medicine","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001137542,0.00009151672,0.0001847665,0.00002442688,0.0001245628,0.00002307044,0.00007373653,0.00004548595,0.000003656876],"category_scores_gemma":[0.00001477263,0.00005301647,0.00006427638,0.0001109791,0.0001707714,0.00002309807,0.00001972985,0.00006730513,2.899912e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002691843,"about_ca_system_score_gemma":0.00001460225,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008780831,"about_ca_topic_score_gemma":0.000006995916,"domain_scores_codex":[0.9993516,0.00008695471,0.0001560953,0.0001576082,0.00009025578,0.0001574531],"domain_scores_gemma":[0.999493,0.0002576497,0.00005948628,0.0001333509,0.00002936712,0.00002715567],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003208965,0.001148685,0.01179987,0.002130346,0.002283011,0.000004183484,0.003788782,0.00764531,0.9202271,0.01485732,0.0002672099,0.03552736],"study_design_scores_gemma":[0.002194903,0.001178532,0.00438164,0.002614409,0.002603319,0.00001330615,0.0004774276,0.677426,0.3001831,0.007758268,0.0008467704,0.0003223312],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9860962,0.007482182,0.002654503,0.002190373,0.0002755265,0.001009077,0.00001892612,0.00003660138,0.0002365781],"genre_scores_gemma":[0.9973171,0.00006780996,0.00201749,0.0001428122,0.0002712968,0.0001569076,0.000008948075,0.00001324343,0.000004380401],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6697807,"threshold_uncertainty_score":0.2161949,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04953710312332465,"score_gpt":0.29479297340896,"score_spread":0.2452558702856353,"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."}}