{"id":"W2300765041","doi":"10.1111/his.12966","title":"The application of next‐generation sequencing‐based molecular diagnostics in endometrial stromal sarcoma","year":2016,"lang":"en","type":"article","venue":"Histopathology","topic":"Uterine Myomas and Treatments","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal Alexandra Hospital; Vancouver General Hospital; University of British Columbia; University of Alberta","funders":"Cancer Research UK; University of Alberta","keywords":"Endometrial stromal sarcoma; Fluorescence in situ hybridization; Biology; Sarcoma; Polymerase chain reaction; Multiplex; Fusion gene; Multiplex polymerase chain reaction; Immunophenotyping; Reverse transcription polymerase chain reaction; Stromal cell; Pathology; Cancer research; Molecular biology; Medicine; Gene; Bioinformatics; Genetics; Flow cytometry; Gene expression; Chromosome","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001419252,0.00007214003,0.0001591644,0.0001012716,0.00003011869,0.000002565261,0.00005086596,0.00005590994,0.000009074473],"category_scores_gemma":[0.0002939809,0.00004237892,0.00004345189,0.0001126864,0.00008782197,0.00002075512,0.00001596654,0.0000395345,0.00000988479],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001764682,"about_ca_system_score_gemma":0.00008505045,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005397568,"about_ca_topic_score_gemma":0.00004893488,"domain_scores_codex":[0.9993424,0.00006941248,0.0002154842,0.0001484053,0.00009769563,0.0001265671],"domain_scores_gemma":[0.9994194,0.0001635206,0.0000872755,0.0002513714,0.00004795014,0.00003051284],"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":[0.0001342503,0.00009867973,0.04852001,0.000007047149,0.000003308536,0.0001849833,0.00002328439,0.000003695691,0.9269933,0.003996056,0.00003749511,0.01999787],"study_design_scores_gemma":[0.02466691,0.004357804,0.5676045,0.0001033547,0.0002895465,0.0004311499,0.00003170702,0.003203386,0.3681416,0.001403892,0.02939118,0.0003749806],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9786236,0.0004347758,0.01950783,0.0007400087,0.0001555662,0.0002796177,0.000007498862,0.00001312679,0.0002379217],"genre_scores_gemma":[0.998051,0.00005263362,0.001589326,0.00008404745,0.00007432579,0.00007233609,0.00001939238,0.000009313077,0.00004762039],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5588518,"threshold_uncertainty_score":0.1728162,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04184720042033522,"score_gpt":0.2822729648724952,"score_spread":0.24042576445216,"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."}}