{"id":"W2256927727","doi":"10.69645/trzu3116","title":"Quantitative CNV testing in molecular diagnostics","year":2009,"lang":"en","type":"article","venue":"˜The œbiomedical & life sciences collection.","topic":"Ultrasound and Hyperthermia Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computational biology; Medicine; Computer science; Biology","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":[0.000329177,0.0001027716,0.0001150881,0.0001570141,0.0003565714,0.00005474654,0.0002856195,0.00005885351,0.00003317852],"category_scores_gemma":[0.0004739658,0.00007606795,0.00003104586,0.002986647,0.0003499864,0.0000788753,0.00001362157,0.0001895376,0.00004201373],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005311377,"about_ca_system_score_gemma":0.000116868,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004838703,"about_ca_topic_score_gemma":0.00005875186,"domain_scores_codex":[0.9989797,0.0000330981,0.0002207807,0.0001852505,0.0003096817,0.000271504],"domain_scores_gemma":[0.9990323,0.0006701967,0.00002570738,0.0001174946,0.00003586457,0.0001184459],"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":[0.00006555417,0.00251991,0.0227292,0.0001467639,0.0002435096,0.0001487136,0.01178312,0.2181747,0.334913,0.1096277,0.1916411,0.1080067],"study_design_scores_gemma":[0.001192258,0.001206741,0.04966215,0.000155285,0.00005906937,0.00008476546,0.002044235,0.8249728,0.001115795,0.04312633,0.07539587,0.0009847129],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.639344,0.004975614,0.2801549,0.009796419,0.001507568,0.001294521,0.00002771177,0.001146852,0.06175232],"genre_scores_gemma":[0.9920534,0.00008640959,0.007009992,0.0006375998,0.00008270972,0.00004196719,0.000002527265,0.000007553027,0.00007779765],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6067981,"threshold_uncertainty_score":0.3101961,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02277392456898749,"score_gpt":0.2660952958617511,"score_spread":0.2433213712927636,"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."}}