{"id":"W2009266771","doi":"10.2174/156802611795429176","title":"Finding New Hits in Neglected Disease Projects: Target or Phenotypic Based Screening?","year":2011,"lang":"en","type":"article","venue":"Current Topics in Medicinal Chemistry","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"Discovery Centre","funders":"Broad Institute; Novartis Foundation","keywords":"Phenotypic screening; Disease; Phenotype; Computational biology; Medicine; Data science; Computer science; Biology; Genetics; Internal medicine; Gene","routes":{"ca_aff":true,"ca_fund":false,"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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002320616,0.0002325662,0.0006769501,0.0002458888,0.00006210179,0.00002357244,0.0003751926,0.0001432226,0.002123562],"category_scores_gemma":[0.005190222,0.0002672573,0.00007064945,0.0004120461,0.00006668216,0.0001857925,0.00005222892,0.0004979669,0.00008322464],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005179449,"about_ca_system_score_gemma":0.0006797505,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003710247,"about_ca_topic_score_gemma":0.00007240842,"domain_scores_codex":[0.9963645,0.00009860638,0.002309606,0.0005960267,0.000135916,0.0004953636],"domain_scores_gemma":[0.9981421,0.0002591328,0.0007698972,0.0004310926,0.0000336777,0.0003640747],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003155029,0.0005340331,0.9691184,0.003304932,0.00002824284,0.00004350782,0.005168585,0.0001281087,0.00001347341,0.002741955,0.01501045,0.003592773],"study_design_scores_gemma":[0.01327542,0.0002146859,0.7393329,0.006382363,0.00004733879,0.00001221533,0.00272813,0.05924137,0.0005688585,0.03934546,0.1364474,0.002403986],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9273075,0.01844274,0.02426602,0.0136138,0.002986797,0.001989246,0.0002263068,0.0001978983,0.01096974],"genre_scores_gemma":[0.9805002,0.0002068977,0.01120274,0.003320554,0.002392386,0.0002259986,0.0002430809,0.00006798652,0.001840183],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2297856,"threshold_uncertainty_score":0.9999779,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4963976006319916,"score_gpt":0.4357863922136876,"score_spread":0.06061120841830392,"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."}}