{"id":"W4210304078","doi":"10.20944/preprints202201.0474.v1","title":"Application of Biosensors in Cancers, An Overview","year":2022,"lang":"en","type":"preprint","venue":"Preprints.org","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Emergent BioSolutions (Canada)","funders":"","keywords":"Biosensor; Analyte; Cancer detection; Biomarker; Cancer biomarkers; Cancer; Nanotechnology; Function (biology); Computer science; Medicine; Computational biology; Biology; Chemistry; Materials science; 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":[0.001583108,0.001769087,0.001456554,0.004077482,0.0005874038,0.002358629,0.001685435,0.003639649,0.003528248],"category_scores_gemma":[0.001320022,0.0009787831,0.00123794,0.003043639,0.001163983,0.00317031,0.001590716,0.00339541,0.005389815],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001240651,"about_ca_system_score_gemma":0.0007573265,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007833645,"about_ca_topic_score_gemma":0.0005732177,"domain_scores_codex":[0.9987979,0.000231106,0.00007915303,0.0002308901,0.0005437264,0.0001171492],"domain_scores_gemma":[0.99929,0.0003028555,0.00004756212,0.0000475981,0.0002626879,0.00004932348],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001520161,0.000292709,0.0007885645,0.01674496,0.0001876001,0.0007889163,0.0002941198,0.001923023,0.05310185,0.03822931,0.04989217,0.8376047],"study_design_scores_gemma":[0.0000103066,0.000228398,0.0007324861,0.001284707,0.00007360317,0.003042959,0.0001084276,0.001199341,0.01712777,0.01368753,0.9624361,0.0000683484],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0006248131,0.9790936,0.01118127,0.001193011,0.001164573,0.00003689065,0.00004950469,0.0001061643,0.00655024],"genre_scores_gemma":[0.005721943,0.9805005,0.00673594,0.001058616,0.001409743,0.0000765773,0.0001269652,0.00003041062,0.004339337],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.004077482,"threshold_uncertainty_score":0.01180315,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1152014295304953,"score_gpt":0.3958355022325039,"score_spread":0.2806340727020086,"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."}}