{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01049804,0.002828751,0.002848972,0.005402835,0.0009126016,0.002851493,0.003550943,0.0009803888,0.05267263],"category_scores_gemma":[0.01874448,0.00237678,0.002811831,0.004053468,0.0009253338,0.002789307,0.003774235,0.003537066,0.03030302],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007797434,"about_ca_system_score_gemma":0.003828546,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001329744,"about_ca_topic_score_gemma":0.002811768,"domain_scores_codex":[0.9937584,0.001655317,0.001216421,0.001053406,0.00195158,0.0003648282],"domain_scores_gemma":[0.9843078,0.008843089,0.001881537,0.002649371,0.001836047,0.0004821797],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00188143,0.0002913071,0.009893943,0.007199428,0.001595145,0.0009333555,0.0006589366,0.007914969,0.03786308,0.01067532,0.7445822,0.1765109],"study_design_scores_gemma":[0.0009273867,0.0005547362,0.02785949,0.001113775,0.0006360604,0.001495205,0.0002563146,0.03791018,0.05367852,0.03731368,0.8376225,0.0006322015],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.00580513,0.001008795,0.4297092,0.0004358594,0.0005291775,0.001331972,0.2174178,0.3391672,0.004594819],"genre_scores_gemma":[0.01969951,0.001423408,0.6392823,0.0008583237,0.0002444469,0.01240867,0.2219561,0.09709901,0.007028183],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.05267263,"threshold_uncertainty_score":0.1762075,"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."}}