{"id":"W2886611301","doi":"10.1177/1093526618790747","title":"Sarcoma Subgrouping by Detection of Fusion Transcripts Using NanoString nCounter Technology","year":2018,"lang":"en","type":"article","venue":"Pediatric and Developmental Pathology","topic":"Molecular Biology Techniques and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Hospital for Sick Children","funders":"","keywords":"Sarcoma; Fusion gene; Polymerase chain reaction; Fusion transcript; Reverse transcription polymerase chain reaction; Fusion; Computational biology; Biology; Medicine; Gene; Pathology; Messenger RNA; 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":[0.001237442,0.000344452,0.0002660633,0.001547984,0.0003286049,0.0004849804,0.0004379531,0.0005860868,0.00123447],"category_scores_gemma":[0.001354351,0.0002227477,0.0002796585,0.0006435004,0.0006772391,0.0004218463,0.0004676785,0.0004183093,0.0003830763],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005734859,"about_ca_system_score_gemma":0.0003709983,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009287299,"about_ca_topic_score_gemma":0.00238312,"domain_scores_codex":[0.9986621,0.0001745447,0.0001283827,0.0004683691,0.0004547722,0.0001118248],"domain_scores_gemma":[0.9992655,0.0002582543,0.0002318107,0.00008881574,0.0001211723,0.00003452776],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001202535,0.00002631316,0.03230731,0.000129756,0.00003819906,0.0002930848,0.0001995282,0.0004326046,0.9501796,0.0004188452,0.0002622144,0.01559234],"study_design_scores_gemma":[0.00001310483,0.0002057757,0.06350192,0.00003870107,0.00008447514,0.0030293,0.0002338242,0.005574591,0.917887,0.0007003236,0.008704579,0.00002635077],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9024134,0.002081087,0.08991635,0.0001929521,0.00003983478,0.00024581,0.0009951782,0.0005572413,0.003558086],"genre_scores_gemma":[0.9130011,0.0009910762,0.08240473,0.0001824803,0.00001849723,0.00039623,0.001324707,0.00006804169,0.001613205],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001547984,"threshold_uncertainty_score":0.006544292,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007068198728386158,"score_gpt":0.2329584716135512,"score_spread":0.2258902728851651,"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."}}