{"id":"W4211026938","doi":"10.1016/j.bpj.2021.11.1368","title":"MDAnalysis 2.0 and beyond: fast and interoperable, community driven simulation analysis","year":2022,"lang":"en","type":"article","venue":"Biophysical Journal","topic":"Machine Learning in Materials Science","field":"Materials Science","cited_by":51,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Interoperability; Python (programming language); Workflow; Variety (cybernetics); Scope (computer science); Scripting language; Data science; Computational science; Software engineering; World Wide Web; Programming language; Artificial intelligence; Database","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":[0.003521591,0.001457201,0.001334759,0.001538935,0.001102071,0.002343856,0.004155752,0.001819391,0.01377589],"category_scores_gemma":[0.01092353,0.001193431,0.002069279,0.001260531,0.0005592489,0.00329621,0.003402831,0.00345495,0.004579463],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008996002,"about_ca_system_score_gemma":0.003624732,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01399711,"about_ca_topic_score_gemma":0.01818974,"domain_scores_codex":[0.998792,0.0004495106,0.00008589013,0.000176111,0.0003734397,0.0001231517],"domain_scores_gemma":[0.9958269,0.001777816,0.0001539188,0.001085236,0.0008068405,0.0003491824],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001066498,0.001002527,0.01266197,0.0008360282,0.001379342,0.000409747,0.000998953,0.6265383,0.009357519,0.06778905,0.1391176,0.1388424],"study_design_scores_gemma":[0.0001029933,0.00003264411,0.0004230132,0.00003012859,0.00003357336,0.00002688085,0.0000519582,0.961083,0.002010708,0.01889973,0.0172563,0.00004908712],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.04690956,0.0004548164,0.7737762,0.001290426,0.0006980874,0.0004895114,0.01430539,0.1503852,0.01169086],"genre_scores_gemma":[0.3279717,0.000559901,0.6039478,0.0007196952,0.000169401,0.001700609,0.02967405,0.02907759,0.006179206],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.01399711,"threshold_uncertainty_score":0.04608494,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01314188551590625,"score_gpt":0.2754586698983079,"score_spread":0.2623167843824016,"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."}}