{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004315151,0.0001350558,0.0002443624,0.0001277659,0.0001520361,0.00001969778,0.0002238195,0.00008599948,0.00003065518],"category_scores_gemma":[0.0001409444,0.0001089667,0.00004915116,0.0002043018,0.000263321,0.000004991536,0.0002937137,0.0001884908,0.000004566967],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007860822,"about_ca_system_score_gemma":0.00003029953,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003085443,"about_ca_topic_score_gemma":0.00001817837,"domain_scores_codex":[0.9988335,0.000110728,0.0001895644,0.0003227066,0.0002000151,0.0003434964],"domain_scores_gemma":[0.9991508,0.00003682846,0.00004658621,0.0003954523,0.0002686461,0.000101659],"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":[0.0001275721,0.0001156481,0.0008218594,0.00001744583,0.00005460189,0.000004045952,0.0001007206,8.840264e-7,0.988223,0.001667085,0.002583986,0.006283215],"study_design_scores_gemma":[0.001001545,0.00153606,0.0414766,0.00002714388,0.000009738968,0.00001706842,0.0005863871,0.0001578439,0.8684083,0.001140927,0.08539579,0.0002426337],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.990455,0.004512877,0.0001350611,0.0005697394,0.0000289391,0.0002040819,0.0001025527,0.000008931091,0.00398285],"genre_scores_gemma":[0.9957473,0.002983328,0.0007985036,0.0001435207,0.00006217856,0.000004691885,0.00007304669,0.00001111265,0.0001763601],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1198147,"threshold_uncertainty_score":0.4443532,"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."}}