{"id":"W3092253816","doi":"10.3390/jpm10040162","title":"Circulating miR-1246 Targeting UBE2C, TNNI3, TRAIP, UCHL1 Genes and Key Pathways as a Potential Biomarker for Lung Adenocarcinoma: Integrated Biological Network Analysis","year":2020,"lang":"en","type":"article","venue":"Journal of Personalized Medicine","topic":"MicroRNA in disease regulation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"China Postdoctoral Science Foundation","keywords":"Biomarker; Adenocarcinoma; Gene; Medicine; Computational biology; Cancer research; Bioinformatics; Biology; Genetics; Cancer; Internal 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003327844,0.0004209765,0.0005438143,0.001480299,0.0003056265,0.0006738019,0.0002475485,0.0002283932,0.001915381],"category_scores_gemma":[0.000511615,0.0002386411,0.000853867,0.001399308,0.0001710118,0.0003539925,0.0004267775,0.0002982873,0.0003178204],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004192812,"about_ca_system_score_gemma":0.0004633534,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002348573,"about_ca_topic_score_gemma":0.003292246,"domain_scores_codex":[0.9996953,0.00003444977,0.00002205769,0.0001505956,0.00004875462,0.00004893246],"domain_scores_gemma":[0.9998084,0.00005649045,0.00007287959,0.000009956923,0.00002196199,0.00003044062],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002656373,0.0002596097,0.6955634,0.00126994,0.001601518,0.0009799408,0.0003499913,0.02238192,0.1605131,0.001778415,0.00394697,0.1086987],"study_design_scores_gemma":[0.0001054504,0.0005758061,0.7162188,0.0001145594,0.001762649,0.00158029,0.000398183,0.2226596,0.04166647,0.004693447,0.01013577,0.00008886655],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9685873,0.002803154,0.01226004,0.0001769455,0.00002138424,0.00008874685,0.01359781,0.0003491194,0.002115556],"genre_scores_gemma":[0.9757401,0.0009828456,0.009926593,0.00008576747,0.00001652397,0.0001650426,0.01166467,0.00003653846,0.001381932],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002348573,"threshold_uncertainty_score":0.006407619,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02865833013505028,"score_gpt":0.2760305813447299,"score_spread":0.2473722512096796,"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."}}