{"id":"W2072750870","doi":"10.1038/npre.2010.5443.1","title":"Keynote: A renaissance for the point mutation: from legacy data to semantic web service","year":2010,"lang":"en","type":"preprint","venue":"Nature Precedings","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Computer science; Mutation; Information retrieval; Annotation; Population; World Wide Web; Visualization; Conceptualization; Artificial intelligence; Genetics; 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":[0.01631851,0.000870669,0.0008892175,0.002023612,0.002436211,0.01214603,0.002645935,0.005143433,0.02595453],"category_scores_gemma":[0.02105838,0.0007450709,0.001440534,0.002309572,0.004379153,0.02115207,0.00830853,0.0110729,0.01507721],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002812115,"about_ca_system_score_gemma":0.003223118,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003670739,"about_ca_topic_score_gemma":0.002533823,"domain_scores_codex":[0.9934255,0.001699823,0.0004361964,0.001053759,0.002827433,0.0005573531],"domain_scores_gemma":[0.9863147,0.004206746,0.0003801441,0.003222978,0.003866629,0.002008868],"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":[0.000400618,0.00009051606,0.0007935187,0.0003993872,0.00005383442,0.0005889327,0.001551527,0.001503435,0.006879692,0.3927106,0.4428338,0.1521942],"study_design_scores_gemma":[0.00002807439,0.00005889859,0.0002762885,0.0002335339,0.00002303205,0.0002783994,0.000492784,0.003450586,0.003539548,0.08600395,0.9055478,0.00006720063],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.006452223,0.004684828,0.6097877,0.2568859,0.05977201,0.0003089919,0.002549229,0.01360278,0.04595629],"genre_scores_gemma":[0.1487455,0.01561936,0.4354595,0.06981224,0.03856368,0.000816562,0.008737625,0.01640749,0.265838],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.02595453,"threshold_uncertainty_score":0.0868265,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03738788146197312,"score_gpt":0.3324161186905119,"score_spread":0.2950282372285387,"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."}}