{"id":"W1537930344","doi":"10.1002/ddr.21211","title":"Opportunities and Challenges Provided by Cloud Repositories for Bioinformatics‐Enabled Drug Discovery","year":2014,"lang":"en","type":"article","venue":"Drug Development Research","topic":"Scientific Computing and Data Management","field":"Decision Sciences","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University and Génome Québec Innovation Centre","funders":"","keywords":"Cloud computing; Data science; Computer science; Big data; Data curation; Process (computing); Data management; Data mining","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":["metaresearch","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.03051634,0.0001848582,0.0003021999,0.0005699899,0.001117597,0.00269201,0.001203505,0.00004138847,0.000017759],"category_scores_gemma":[0.004354515,0.0001317782,0.00004573257,0.0004833121,0.0002628616,0.0009362605,0.001357105,0.0001605884,0.00006308971],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007808329,"about_ca_system_score_gemma":0.000296365,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005174542,"about_ca_topic_score_gemma":0.00007844818,"domain_scores_codex":[0.9945737,0.0004168452,0.0008463439,0.0008034327,0.00268353,0.000676187],"domain_scores_gemma":[0.9942661,0.003637111,0.0001854423,0.0009950527,0.0006966917,0.0002196256],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004964523,0.00006972395,0.0003304473,0.0002049954,0.00002533505,0.000002252796,0.009864869,0.000004189298,0.00003337364,0.0167669,0.7499831,0.2226652],"study_design_scores_gemma":[0.0003497206,0.00002979827,0.0006255994,0.00005640941,0.000003111792,0.000001772327,0.01932134,0.003004941,0.001470525,0.005222762,0.9697106,0.000203367],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7136453,0.009784387,0.05449849,0.1036637,0.01003223,0.006911684,0.0001969615,0.0006943937,0.1005728],"genre_scores_gemma":[0.5083049,0.0014785,0.03095874,0.0003471421,0.0007083488,0.0005597848,0.000276956,0.00005677752,0.4573089],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3567361,"threshold_uncertainty_score":0.9983433,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2780948536326209,"score_gpt":0.39841421853324,"score_spread":0.1203193649006191,"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."}}