{"id":"W2125204079","doi":"10.1186/1756-9966-31-79","title":"A comparison of Direct sequencing, Pyrosequencing, High resolution melting analysis, TheraScreen DxS, and the K-ras StripAssay for detecting KRAS mutations in non small cell lung carcinomas","year":2012,"lang":"en","type":"article","venue":"Journal of Experimental & Clinical Cancer Research","topic":"Colorectal Cancer Treatments and Studies","field":"Medicine","cited_by":56,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Ministerstvo Průmyslu a Obchodu; Ministerstvo Zdravotnictví Ceské Republiky","keywords":"KRAS; Sanger sequencing; High Resolution Melt; Pyrosequencing; Biology; Cancer research; Lung cancer; DNA sequencing; Colorectal cancer; Cancer; Computational biology; Gene; Internal medicine; Polymerase chain reaction; Medicine; Genetics","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":[0.006574908,0.0009111341,0.001103591,0.002025039,0.0003090806,0.001110761,0.001150143,0.001052067,0.0005754091],"category_scores_gemma":[0.007276136,0.0005806806,0.000690227,0.0009823706,0.0006598557,0.0005018638,0.0007550576,0.0007179867,0.0003779168],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005271291,"about_ca_system_score_gemma":0.0005736913,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007011506,"about_ca_topic_score_gemma":0.001870949,"domain_scores_codex":[0.9899611,0.003700161,0.0004927851,0.001655751,0.00394346,0.000246619],"domain_scores_gemma":[0.9942307,0.003177975,0.0006119059,0.0005533376,0.001195689,0.0002303636],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00470166,0.0005387441,0.05893555,0.0009360684,0.0004685266,0.0001579769,0.0005008918,0.002665721,0.8096662,0.0004761186,0.0003776953,0.1205748],"study_design_scores_gemma":[0.0001404947,0.009109408,0.1130407,0.00007920113,0.0007709261,0.002179991,0.0003169414,0.03092366,0.8397489,0.0003914106,0.003147797,0.0001506469],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9423185,0.007236973,0.04678396,0.0001553482,0.00013089,0.0003036791,0.0006347493,0.0004043547,0.00203156],"genre_scores_gemma":[0.8538584,0.002313376,0.1394091,0.0001932438,0.00006776189,0.000312686,0.001265233,0.0001222927,0.002457981],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006574908,"threshold_uncertainty_score":0.03477186,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2112603066991464,"score_gpt":0.5189624052316912,"score_spread":0.3077020985325448,"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."}}