{"id":"W1964255443","doi":"10.1371/journal.pbio.1002033","title":"Finding Our Way through Phenotypes","year":2015,"lang":"en","type":"article","venue":"PLoS Biology","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":222,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; Simon Fraser University","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Cancer Institute; National Human Genome Research Institute; Biotechnology and Biological Sciences Research Council; National Science Foundation","keywords":"Phenomics; Biology; Bottleneck; Data science; Genomics; Systematics; Phenotype; Systems biology; Computational biology; Ecology; Computer science; Genome; Genetics; Taxonomy (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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007045968,0.0008742961,0.0008081544,0.003041078,0.001942595,0.008789867,0.001705921,0.00141855,0.01333012],"category_scores_gemma":[0.03184371,0.0004870032,0.001342562,0.003227581,0.006622014,0.01517358,0.004812764,0.003478705,0.003923746],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00162721,"about_ca_system_score_gemma":0.003039824,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004454808,"about_ca_topic_score_gemma":0.00436766,"domain_scores_codex":[0.9960264,0.001493593,0.000307396,0.001226584,0.0007883474,0.0001575674],"domain_scores_gemma":[0.9897206,0.004291371,0.0009305138,0.003091485,0.001433076,0.000532929],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001620684,0.00008039374,0.04261888,0.0009068168,0.0001781792,0.001017449,0.01584959,0.001998405,0.004862915,0.5647018,0.05965101,0.3079725],"study_design_scores_gemma":[0.0000113415,0.00003902521,0.01336675,0.0007285632,0.0001158496,0.0009018735,0.006947821,0.002336653,0.002538723,0.5515728,0.4213453,0.00009517914],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08013587,0.007299105,0.6694259,0.08599747,0.002514962,0.0003255455,0.01866098,0.005578357,0.1300618],"genre_scores_gemma":[0.4780569,0.01257951,0.4431258,0.01379006,0.0007571402,0.0005404897,0.01430067,0.004371694,0.03247779],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01333012,"threshold_uncertainty_score":0.04459375,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09074615135526791,"score_gpt":0.3319444958987222,"score_spread":0.2411983445434543,"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."}}