{"id":"W2031410708","doi":"","title":"Mapping the Cellular Response to Small Molecules Using Chemogenomic Fitness Signatures","year":2013,"lang":"en","type":"article","venue":"DSpace@MIT (Massachusetts Institute of Technology)","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":264,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Haploinsufficiency; Computational biology; Gene; Biology; Profiling (computer programming); Gene expression profiling; Genetics; Phenotype; Bioinformatics; Gene expression; Computer science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001450653,0.0003374533,0.0003462458,0.0009288741,0.000183534,0.0004828571,0.0001594089,0.000201275,0.0006977893],"category_scores_gemma":[0.0004038392,0.0001209711,0.0002804178,0.0009813219,0.0001860419,0.0002341332,0.0002820887,0.0002623498,0.0002082676],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003656427,"about_ca_system_score_gemma":0.0002519207,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00121131,"about_ca_topic_score_gemma":0.002036545,"domain_scores_codex":[0.9998875,0.00001353261,0.000005209564,0.00004756438,0.00003171518,0.00001449305],"domain_scores_gemma":[0.9997206,0.00009471899,0.00009384932,0.0000301556,0.00003585906,0.00002483451],"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":[0.0001089878,0.000031228,0.01625691,0.0000803074,0.00004091617,0.00005459004,0.00002561919,0.003181203,0.9696471,0.0003476626,0.00008180678,0.01014363],"study_design_scores_gemma":[0.00002266321,0.0004152794,0.4020613,0.00001915464,0.000191342,0.0003132145,0.0001790737,0.06084986,0.5294405,0.002645912,0.003816268,0.00004548393],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9792991,0.0004175959,0.01477434,0.00007537271,0.00000434406,0.0000414874,0.003640723,0.0002624914,0.001484576],"genre_scores_gemma":[0.985413,0.0005344785,0.009835867,0.00005162625,0.000003414385,0.00007559776,0.003470064,0.00004531427,0.0005705847],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00121131,"threshold_uncertainty_score":0.002652943,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01407983085921933,"score_gpt":0.2153034869754312,"score_spread":0.2012236561162118,"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."}}