{"id":"W4236181331","doi":"10.2172/1375720","title":"Biological and Environmental Research Exascale Requirements Review. An Office of Science review sponsored jointly by Advanced Scientific Computing Research and Biological and Environmental Research, March 28-31, 2016, Rockville, Maryland","year":2016,"lang":"en","type":"report","venue":"","topic":"Environmental Monitoring and Data Management","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Pacific Centre for Reproductive Medicine; University of Toronto","funders":"","keywords":"Transformative learning; Environmental research; Earth system science; Atmospheric research; Exascale computing; Portfolio; Biological sciences; Supercomputer; Computer science; Data science; Engineering; Environmental resource management; Environmental science; Sociology; Ecology; Geography; Meteorology; Business","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","metaepi_narrow","sts","insufficient_payload"],"consensus_categories":["sts"],"category_scores_codex":[0.04777689,0.0006036366,0.001106855,0.0008726717,0.002539356,0.0003364774,0.001383507,0.0003529204,0.00176041],"category_scores_gemma":[0.001194534,0.0004081532,0.00008229115,0.0009041391,0.01877667,0.0008020106,0.00264232,0.001442462,0.000159276],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002737707,"about_ca_system_score_gemma":0.0002760012,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004985253,"about_ca_topic_score_gemma":0.00004053362,"domain_scores_codex":[0.9856181,0.002663361,0.001284641,0.003124801,0.005322985,0.001986174],"domain_scores_gemma":[0.9953465,0.001787549,0.0003527534,0.001386346,0.0001396964,0.0009871002],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0007646432,0.001204113,0.2938575,0.006984103,0.0001369813,0.0001761428,0.0001154194,0.000001697232,0.02559672,0.00001290554,0.07257375,0.5985761],"study_design_scores_gemma":[0.001770092,0.008735165,0.4763042,0.02297826,0.00009335276,0.0003560199,0.002137938,0.0001733925,0.00129292,0.0004507448,0.4837635,0.001944416],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"review","genre_scores_codex":[0.7082257,0.2787888,0.000007444316,0.0004587623,0.0003693063,0.003166139,0.002441217,0.0000253525,0.006517323],"genre_scores_gemma":[0.3730153,0.6186976,0.0004675042,0.00004304063,0.0001292812,0.00002157143,0.002375523,0.00001856832,0.005231564],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5966316,"threshold_uncertainty_score":0.999837,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1828089823163314,"score_gpt":0.3913598648997851,"score_spread":0.2085508825834536,"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."}}