{"id":"W4301283137","doi":"10.1007/978-3-319-21410-8","title":"Computational Science and Its Applications -- ICCSA 2015","year":2015,"lang":"en","type":"book","venue":"Lecture notes in computer science","topic":"Scientific Computing and Data Management","field":"Decision Sciences","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Set (abstract data type); Volume (thermodynamics); Computational science; Programming language","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","sts","scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.02149351,0.0004117416,0.000526578,0.002781923,0.0009223917,0.003077709,0.006236799,0.0001525678,0.00003828915],"category_scores_gemma":[0.004999624,0.000333239,0.00006422828,0.006470782,0.003176687,0.00101164,0.004460288,0.0005393064,0.0004508753],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007725718,"about_ca_system_score_gemma":0.005348456,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001000898,"about_ca_topic_score_gemma":0.00002765055,"domain_scores_codex":[0.9868759,0.0000922633,0.0009348488,0.003245821,0.008065417,0.0007857722],"domain_scores_gemma":[0.9912157,0.002326128,0.0004832281,0.002013126,0.003456237,0.000505574],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00000549827,0.00005982734,0.00007194452,0.00001940518,0.000005294113,0.00001503173,0.0005817983,0.1534371,0.0000218415,0.006950427,0.02324651,0.8155853],"study_design_scores_gemma":[0.0001822124,0.00004764624,0.0002329066,0.00006330181,0.000006596084,0.00003149516,0.000001947318,0.6388074,0.00002413987,0.2807647,0.07947733,0.0003602365],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0002456733,0.0008108811,0.9863068,0.001392292,0.002139931,0.0007454117,0.0000544016,0.00009979303,0.008204786],"genre_scores_gemma":[0.4353556,0.00005573977,0.5274631,0.007147737,0.003664273,0.0001654992,0.0001804605,0.0001273121,0.02584031],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8152251,"threshold_uncertainty_score":0.999912,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0835687946524721,"score_gpt":0.3767723353820583,"score_spread":0.2932035407295862,"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."}}