{"id":"W2139932193","doi":"10.1093/nar/gkp934","title":"T3DB: a comprehensively annotated database of common toxins and their targets","year":2009,"lang":"en","type":"article","venue":"Nucleic Acids Research","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":168,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Institute for Nanotechnology; University of Alberta","funders":"Canadian Institutes of Health Research; Genome Alberta; Ministry of Advanced Education, Government of Alberta; Genome Canada","keywords":"Biology; Computational biology; Database; Computer science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002578043,0.002455874,0.002889618,0.0130236,0.001708445,0.004279147,0.00333204,0.002945591,0.03123411],"category_scores_gemma":[0.007409952,0.0009432916,0.00221507,0.01733993,0.000666319,0.004073483,0.003278739,0.002345918,0.0286903],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002134888,"about_ca_system_score_gemma":0.00791423,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009370782,"about_ca_topic_score_gemma":0.007665269,"domain_scores_codex":[0.9978098,0.0003241847,0.000635098,0.0004283894,0.0006196087,0.0001830039],"domain_scores_gemma":[0.9938895,0.001701377,0.001339039,0.0008185196,0.001438275,0.0008133039],"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":[0.003786073,0.0005809562,0.01142382,0.02522199,0.0006591405,0.003099686,0.0008906967,0.006250104,0.05127346,0.02248208,0.7173244,0.1570075],"study_design_scores_gemma":[0.000252831,0.0002139439,0.006330919,0.0011365,0.0003881627,0.001182199,0.0002277325,0.002307333,0.00915193,0.006432211,0.9722345,0.0001417492],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.007366661,0.00992238,0.02381823,0.0008917338,0.0002750265,0.0003419698,0.9301887,0.01358005,0.01361523],"genre_scores_gemma":[0.007758006,0.005136332,0.02378544,0.000395629,0.0000689107,0.0002914157,0.9597691,0.0007892469,0.002005916],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.03123411,"threshold_uncertainty_score":0.1044886,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03866693584936604,"score_gpt":0.3330547575771503,"score_spread":0.2943878217277843,"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."}}