{"id":"W4322722666","doi":"10.21203/rs.3.rs-2627227/v1","title":"Therapeutic Target Identification in Pancreatic Ductal Adenocarcinoma: A Comprehensive In-Silico Study employing WGCNA and Trader","year":2023,"lang":"en","type":"preprint","venue":"Research Square","topic":"Pancreatic and Hepatic Oncology Research","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Biology; Computational biology; Gene; FYN; Identification (biology); Pancreatic cancer; Bioinformatics; Cancer research; Cancer; Genetics; Signal transduction; Tyrosine kinase","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":[0.00260854,0.001230532,0.001368383,0.00158241,0.0005020638,0.0008300364,0.0007633472,0.0007793144,0.001424296],"category_scores_gemma":[0.002223313,0.0003941874,0.002743312,0.001249889,0.0003508486,0.000449929,0.0005950817,0.0005240576,0.0002484887],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005635236,"about_ca_system_score_gemma":0.001024192,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003458577,"about_ca_topic_score_gemma":0.003595421,"domain_scores_codex":[0.9995428,0.0001968568,0.00002870464,0.000112957,0.00006755096,0.00005107974],"domain_scores_gemma":[0.9991032,0.0006507183,0.00007048363,0.00006175086,0.00007983377,0.00003410024],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007569226,0.0004670938,0.03880916,0.0008794271,0.0009584134,0.0005603918,0.00008171092,0.9069695,0.01866986,0.001711263,0.001511846,0.02862444],"study_design_scores_gemma":[0.00003140245,0.0001977573,0.003570206,0.00001559618,0.0002018778,0.00008878641,0.00003445685,0.9917479,0.002787719,0.0006306851,0.0006805893,0.00001309952],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9287402,0.001392455,0.06287456,0.0003201674,0.00006809883,0.0002490311,0.003245827,0.001353221,0.001756466],"genre_scores_gemma":[0.8859288,0.0007924099,0.1028504,0.0001934315,0.0000205572,0.0003108489,0.008761661,0.0001563434,0.0009855814],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003458577,"threshold_uncertainty_score":0.01379544,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2197832160078333,"score_gpt":0.4698625309453435,"score_spread":0.2500793149375102,"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."}}