{"id":"W1156765303","doi":"10.1038/ncomms8485","title":"Caenorhabditis elegans is a useful model for anthelmintic discovery","year":2015,"lang":"en","type":"article","venue":"Nature Communications","topic":"Genetics, Aging, and Longevity in Model Organisms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":246,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Institute for Research in Immunology and Cancer; Canada Research Chairs; Université de Montréal; University of Calgary; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; University of Toronto; National Institute of Neurological Disorders and Stroke; Harvard Stem Cell Institute; National Institutes of Health; National Heart, Lung, and Blood Institute; University of Calgary","keywords":"Caenorhabditis elegans; Anthelmintic; Biology; Nematode; Zebrafish; Drug discovery; Model organism; Population; Computational biology; Resistance (ecology); Effector; Genetics; Bioinformatics; Cell biology; Gene; Ecology; Medicine","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":[0.0002843156,0.000585807,0.0004686925,0.0005746629,0.000594761,0.0004018314,0.0005213487,0.0004603737,0.001122709],"category_scores_gemma":[0.0001781503,0.0001973428,0.0002336925,0.0003567704,0.0002320222,0.0003484267,0.0002957887,0.0007410266,0.0004229889],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000623473,"about_ca_system_score_gemma":0.0006986894,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004704644,"about_ca_topic_score_gemma":0.01214118,"domain_scores_codex":[0.9998065,0.00002654392,0.00001841493,0.00003604128,0.00009345661,0.00001907574],"domain_scores_gemma":[0.9998826,0.00002479059,0.00002733678,0.0000211096,0.0000201004,0.00002412397],"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":[0.0001178993,0.00006004218,0.001033828,0.0002392963,0.00001909304,0.0002181449,0.0000204136,0.0004262387,0.986005,0.001505523,0.001312442,0.009042163],"study_design_scores_gemma":[0.0001359858,0.002409022,0.0171057,0.000228236,0.0001735924,0.001773169,0.0001302689,0.004577462,0.837436,0.002330045,0.1336232,0.00007742002],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8760028,0.03053122,0.03903318,0.002638344,0.0008389435,0.0008397776,0.01559996,0.001771557,0.03274419],"genre_scores_gemma":[0.9039994,0.01725975,0.06079905,0.0003864954,0.0000623674,0.0003641446,0.00482189,0.0001011226,0.01220568],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004704644,"threshold_uncertainty_score":0.009354532,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0377059076743205,"score_gpt":0.3057379535722997,"score_spread":0.2680320458979791,"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."}}