{"id":"W2875864584","doi":"10.1002/advs.201800028","title":"Chemically Propelled Motors Navigate Chemical Patterns","year":2018,"lang":"en","type":"article","venue":"Advanced Science","topic":"Micro and Nano Robotics","field":"Physics and Astronomy","cited_by":64,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Science Foundation of Zhejiang Province; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Molecular motor; Non-equilibrium thermodynamics; Computer science; Chemical Dynamics; Brownian motion; Nanotechnology; Biological system; Variety (cybernetics); Collective behavior; Active matter; Biochemical engineering; Physics; Chemical physics; Materials science; Artificial intelligence; Engineering; Biology","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":[0.0001198675,0.0001139566,0.000111911,0.00002876896,0.0001685235,0.00004278549,0.0004457452,0.00001773635,0.0004129657],"category_scores_gemma":[0.00001337788,0.0000941947,0.00003996415,0.0003496985,0.0005358335,0.0002422643,0.0001391761,0.00009840532,0.000268922],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002375697,"about_ca_system_score_gemma":0.00009751226,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000120808,"about_ca_topic_score_gemma":3.123628e-7,"domain_scores_codex":[0.9988919,0.000005425245,0.0001480782,0.0003522882,0.0002137154,0.0003886236],"domain_scores_gemma":[0.9993672,0.00001451792,0.00006057825,0.0002770902,0.0001412922,0.0001393247],"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":[0.000007624166,0.00003582002,0.004918342,0.000002352677,0.00000253321,4.550588e-7,0.00009690447,0.000008184614,0.9805498,0.001284743,0.00004287238,0.01305041],"study_design_scores_gemma":[0.0002901481,0.000034754,0.0004899707,0.00002526564,0.000004022927,9.433771e-7,0.00003567628,0.0004210955,0.9954869,0.001058859,0.001988648,0.000163716],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9833496,0.00000690258,0.009808636,0.0000500057,0.0001919935,0.0001313281,0.000007376242,0.00003461321,0.006419605],"genre_scores_gemma":[0.9931679,9.801728e-7,0.00600017,0.00007434948,0.0002268226,0.000007447734,0.000004027573,0.000009212149,0.0005091036],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01493714,"threshold_uncertainty_score":0.4521685,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005046186778388973,"score_gpt":0.2542091853079336,"score_spread":0.2491629985295446,"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."}}