{"id":"W2260422212","doi":"10.1371/journal.pone.0131274","title":"PhenStat: A Tool Kit for Standardized Analysis of High Throughput Phenotypic Data","year":2015,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":67,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Human Genome Research Institute; National Institutes of Health; Institute of Genetics; Wellcome Trust; Wellcome","keywords":"Throughput; Phenotype; Computational biology; Computer science; Biology; Genetics; Operating system","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003510112,0.000102409,0.0003811425,0.0000516501,0.00002778571,0.00001092658,0.0003596703,0.0001274115,0.00002178073],"category_scores_gemma":[0.0009040993,0.00008702106,0.0000756209,0.000203784,0.0001298946,0.00000316968,0.0002184181,0.00004417052,0.000002488403],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001015876,"about_ca_system_score_gemma":0.0001091883,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004031138,"about_ca_topic_score_gemma":0.000049547,"domain_scores_codex":[0.9989729,0.00003678072,0.0002257,0.0003424304,0.0002387025,0.0001834959],"domain_scores_gemma":[0.9988267,0.00004206856,0.00009836593,0.0007727905,0.0001904137,0.0000696428],"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":[0.005868485,0.00590426,0.01383745,0.000661109,0.04784295,0.00001044063,0.001098472,0.0001599902,0.7573382,0.001536282,0.07212206,0.0936203],"study_design_scores_gemma":[0.0166356,0.005256222,0.008169231,0.0002416998,0.02149993,0.00000302668,0.001335751,0.01274474,0.7808877,0.00450485,0.1469505,0.001770755],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9624414,0.001209765,0.03388007,0.000389768,0.00005502892,0.0002168199,0.001500093,0.00002729574,0.000279692],"genre_scores_gemma":[0.9236571,0.00009580485,0.07359862,0.0001501259,0.0001489931,0.00002276364,0.001947095,0.00001398634,0.0003655214],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09184954,"threshold_uncertainty_score":0.3548616,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1430479899815878,"score_gpt":0.3158650875558744,"score_spread":0.1728170975742866,"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."}}