{"id":"W3048630142","doi":"10.7554/elife.51850","title":"Modeling the metabolic interplay between a parasitic worm and its bacterial endosymbiont allows the identification of novel drug targets","year":2020,"lang":"en","type":"article","venue":"eLife","topic":"Insect symbiosis and bacterial influences","field":"Agricultural and Biological Sciences","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Hospital for Sick Children","funders":"National Institute of Allergy and Infectious Diseases; Natural Sciences and Engineering Research Council of Canada; National Institutes of Health","keywords":"Identification (biology); Computational biology; Biology; Drug discovery; Drug target; Neglected tropical diseases; Bioinformatics; Ecology; Disease; 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":[0.0000884294,0.0006133696,0.0003292767,0.0002419619,0.0002789778,0.0005560358,0.0003530338,0.0006427406,0.001566785],"category_scores_gemma":[0.000201114,0.0002224683,0.0005972329,0.0002485114,0.0002364334,0.0005475348,0.0002816273,0.0003474265,0.0002428246],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000671657,"about_ca_system_score_gemma":0.000775854,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01162007,"about_ca_topic_score_gemma":0.01069031,"domain_scores_codex":[0.9999641,0.000005944656,0.000002033177,0.00001309846,0.000005909385,0.000008808527],"domain_scores_gemma":[0.9999506,0.00001950509,0.00001183143,0.000004862086,0.000004696702,0.000008490463],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002432464,0.00009460953,0.008717883,0.0001649124,0.00006988947,0.0001468829,0.00003550494,0.9409109,0.0379586,0.004563246,0.000180537,0.006913799],"study_design_scores_gemma":[0.00001900897,0.0001430666,0.001681069,0.000006391194,0.00003385798,0.00003538223,0.0000314529,0.9906476,0.005217692,0.001190364,0.0009839281,0.0000101006],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9631742,0.0005243775,0.0289338,0.0001776351,0.00001908971,0.00003520204,0.001010385,0.0001141838,0.006011135],"genre_scores_gemma":[0.9865177,0.0006964068,0.01020781,0.00002025758,0.000003812252,0.00005772664,0.000455266,0.00001621341,0.002024744],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01162007,"threshold_uncertainty_score":0.02310491,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03575895099142981,"score_gpt":0.2590097486072233,"score_spread":0.2232507976157935,"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."}}