{"id":"W3016862866","doi":"10.1371/journal.pone.0229862","title":"ChemOS: An orchestration software to democratize autonomous discovery","year":2020,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Innovative Microfluidic and Catalytic Techniques Innovation","field":"Engineering","cited_by":146,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vector Institute; University of Toronto; Canadian Institute for Advanced Research; University of British Columbia","funders":"Tata Sons; Division of Chemistry; Natural Sciences and Engineering Research Council of Canada; University of British Columbia; National Science Foundation","keywords":"Software deployment; Orchestration; Computer science; Software; Flexibility (engineering); Modular design; Automation; Software engineering; Data science; Systems engineering; DevOps; Engineering; Operating system","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.00007136471,0.0001302032,0.0001537661,0.00004802783,0.00003912509,0.00005613411,0.0001357213,0.00006996639,0.00005887638],"category_scores_gemma":[0.0000770091,0.0001436133,0.00001626922,0.0004419054,0.00001740191,0.000406289,0.00002780344,0.000149246,0.0000694687],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006753739,"about_ca_system_score_gemma":0.00002815117,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001089073,"about_ca_topic_score_gemma":5.944077e-7,"domain_scores_codex":[0.9992735,0.000007271138,0.0002243879,0.0001802395,0.0001538717,0.0001606626],"domain_scores_gemma":[0.9996413,0.00000969859,0.00002364572,0.0001706593,0.00008973919,0.00006497164],"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":[0.00001125704,0.0001053539,0.0002718982,0.0001004428,0.00004996704,0.000002675239,0.0006486248,0.00004010249,0.9910678,0.001154065,0.002467232,0.00408059],"study_design_scores_gemma":[0.0001120236,0.0001376799,0.0005053277,0.00003905964,0.00001889207,7.048908e-7,0.00004933722,0.002235965,0.9957002,0.0002995933,0.0006916372,0.0002096097],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3957608,0.00002415911,0.6009607,0.000580624,0.00002380289,0.0002827424,0.00003259172,0.001086178,0.001248319],"genre_scores_gemma":[0.9591041,0.000003472577,0.03903443,0.001239089,0.0001973987,0.00005247365,0.0002080985,0.00003985619,0.0001210615],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5633433,"threshold_uncertainty_score":0.585638,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.046391561889842,"score_gpt":0.2252292582226595,"score_spread":0.1788376963328175,"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."}}