{"id":"W2380654641","doi":"10.1073/pnas.1520693113","title":"Cos-Seq for high-throughput identification of drug target and resistance mechanisms in the protozoan parasite <i>Leishmania</i>","year":2016,"lang":"en","type":"article","venue":"Proceedings of the National Academy of Sciences","topic":"Research on Leishmaniasis Studies","field":"Medicine","cited_by":86,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; Centre hospitalier universitaire de Québec","funders":"Canadian Institutes of Health Research; Government of Canada","keywords":"Cosmid; Leishmania; Biology; Computational biology; Drug resistance; Leishmaniasis; Identification (biology); Function (biology); Drug discovery; Leishmania mexicana; Gene; Parasite hosting; Genetics; Bioinformatics; 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":[0.004069504,0.0000868797,0.0002180739,0.0001438423,0.0001601737,0.00001738223,0.0005372239,0.00004566114,0.000002484128],"category_scores_gemma":[0.001758191,0.00004098336,0.00004962228,0.0005630329,0.001059393,0.0003916321,0.00009193662,0.00009379917,3.337128e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000412872,"about_ca_system_score_gemma":0.00004218058,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007498159,"about_ca_topic_score_gemma":0.00000106721,"domain_scores_codex":[0.9977183,0.00001618406,0.0004624748,0.0002650435,0.001369315,0.0001686878],"domain_scores_gemma":[0.9986538,0.0003938264,0.0005090673,0.00001913562,0.0004014241,0.00002274409],"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":[0.0001428369,0.00008661742,0.0127874,0.000380339,0.00002226957,1.122588e-8,0.0007024465,6.870865e-7,0.6520988,0.330786,0.002801182,0.0001914217],"study_design_scores_gemma":[0.000549527,0.00007282096,0.1866973,0.0002762541,0.00001325697,0.000002722371,0.0004323352,0.00002750531,0.5164516,0.2951531,0.0002753458,0.00004827796],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9212914,0.0003407276,0.00004589276,0.07444006,0.00001757902,0.002402651,0.00006480514,0.000009574351,0.001387383],"genre_scores_gemma":[0.994868,0.0001268018,0.004181704,0.0002254093,0.00003816323,0.0002103589,1.683927e-7,0.000004535776,0.0003447947],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1739099,"threshold_uncertainty_score":0.3903376,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0399738987222515,"score_gpt":0.3362389743823639,"score_spread":0.2962650756601124,"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."}}