{"id":"W4407556581","doi":"10.26434/chemrxiv-2025-zhkrf","title":"Democratizing self-driving labs through user-developed automation infrastructure","year":2025,"lang":"en","type":"preprint","venue":"ChemRxiv","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Foundation for Innovation","keywords":"Automation; Critical infrastructure; Self driving; Computer security; Internet privacy; Computer science; World Wide Web; Business; Engineering; Transport engineering","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003928606,0.0005014308,0.0005075696,0.0001910543,0.0003885882,0.0007183252,0.002071548,0.0005329241,0.00000639469],"category_scores_gemma":[0.0001426028,0.0005181759,0.0001761036,0.0006664007,0.00003064577,0.0005541453,0.004296922,0.001027989,0.00004426718],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003071224,"about_ca_system_score_gemma":0.0007976266,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001469461,"about_ca_topic_score_gemma":0.000001867524,"domain_scores_codex":[0.9973241,0.00009809146,0.0006065108,0.001028811,0.0003795441,0.0005629477],"domain_scores_gemma":[0.997888,0.0001706819,0.0004050111,0.001199782,0.0002482987,0.00008823779],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001814667,0.0004193696,0.04468399,0.007696323,0.001762256,0.0002772835,0.085801,0.01537076,0.006281768,0.03456419,0.5794142,0.2237107],"study_design_scores_gemma":[0.0008999004,0.00003412271,0.03792665,0.002817044,0.000132443,0.00004917256,0.00006711725,0.6980219,0.03633319,0.07089426,0.1500514,0.002772806],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1219223,0.000270609,0.8285043,0.001162998,0.02443617,0.0005198768,3.34868e-7,0.002882044,0.02030137],"genre_scores_gemma":[0.097137,0.00007038593,0.896659,0.0008582839,0.003711318,0.00005100539,0.00004543839,0.00004618788,0.001421428],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.6826512,"threshold_uncertainty_score":0.999727,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01714728587668972,"score_gpt":0.2652491449797442,"score_spread":0.2481018591030545,"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."}}