{"id":"W4407953715","doi":"10.1039/d4dd00115j","title":"Atlas: a brain for self-driving laboratories","year":2025,"lang":"en","type":"article","venue":"Digital Discovery","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vector Institute; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; University of Toronto; Canada Foundation for Innovation; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; Canada First Research Excellence Fund; Government of Ontario; Government of Canada; Vector Institute; Canadian Institute for Advanced Research","keywords":"Atlas (anatomy); Medicine; Anatomy","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007804314,0.0006209411,0.0003115019,0.0006926622,0.0006397536,0.002013063,0.001582103,0.0008762647,0.02724154],"category_scores_gemma":[0.001385124,0.0002865474,0.0004343633,0.0004875046,0.001150808,0.002525949,0.003082303,0.001173007,0.008684942],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007494082,"about_ca_system_score_gemma":0.001732703,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001236194,"about_ca_topic_score_gemma":0.001875067,"domain_scores_codex":[0.9996928,0.00006081917,0.0000164339,0.00005658485,0.0001339442,0.00003938497],"domain_scores_gemma":[0.9992647,0.0001621991,0.00003074757,0.0001232525,0.0001805473,0.0002386022],"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":[0.001029742,0.0002618588,0.002012369,0.0006191098,0.0001474633,0.0007703521,0.0008805962,0.003317269,0.05880689,0.1209052,0.3908659,0.4203833],"study_design_scores_gemma":[0.0003622246,0.0005515962,0.002189739,0.0001489701,0.0001531453,0.001328512,0.0002664914,0.01443032,0.02622947,0.06876427,0.8854651,0.0001101215],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0382364,0.004747106,0.6108211,0.0122944,0.002675039,0.0008582993,0.006803971,0.1280626,0.195501],"genre_scores_gemma":[0.3373655,0.004097744,0.5252258,0.007133661,0.000927748,0.001548204,0.006172807,0.005811524,0.1117169],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02724154,"threshold_uncertainty_score":0.0911321,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01123858143881375,"score_gpt":0.2659508058814753,"score_spread":0.2547122244426616,"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."}}