{"id":"W3197238885","doi":"10.1038/s41467-021-25582-8","title":"Reconfigurable multi-component micromachines driven by optoelectronic tweezers","year":2021,"lang":"en","type":"article","venue":"Nature Communications","topic":"Microfluidic and Bio-sensing Technologies","field":"Engineering","cited_by":96,"is_retracted":false,"has_abstract":true,"ca_institutions":"Occupational Cancer Research Centre; Toronto Rehabilitation Institute; University of Toronto","funders":"Engineering and Physical Sciences Research Council; Guangdong Provincial Pearl River Talents Program; Canada First Research Excellence Fund; University of Toronto; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Component (thermodynamics); Microfluidics; Tweezers; Nanotechnology; Multiplexing; Optical tweezers; Computer science; Engineering; Materials science; Electronic engineering; Electrical engineering; Physics; Optics","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":[0.00006491887,0.0001467767,0.0001591154,0.00005811737,0.0001944802,0.00004268495,0.0007455048,0.0003258339,0.00002627167],"category_scores_gemma":[0.00005995766,0.0001471187,0.00006841955,0.0002780754,0.00009578051,0.00005754284,0.0001313779,0.001044252,0.00004030115],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001037625,"about_ca_system_score_gemma":0.00003509439,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001505305,"about_ca_topic_score_gemma":0.0001353737,"domain_scores_codex":[0.9993197,0.00004615638,0.0001764745,0.0001556573,0.00006652088,0.000235487],"domain_scores_gemma":[0.9983918,0.0000839013,0.00002838001,0.001381134,0.00007840618,0.00003637661],"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":[7.773667e-7,0.00006097402,0.0002610265,0.000009263003,0.0000513802,0.00000140989,0.00004337543,0.00002695858,0.8866233,0.0006235522,0.1091609,0.003137082],"study_design_scores_gemma":[0.0002620587,0.000009112068,0.0005826624,0.00003484996,0.00002587394,0.00003292087,0.0001150684,0.005142961,0.4973114,0.0000972189,0.4961313,0.0002545729],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.3567788,0.5988129,0.004100962,0.01934251,0.0009621315,0.0005189309,0.0002620266,0.004667975,0.0145538],"genre_scores_gemma":[0.9662671,0.01518593,0.01755801,0.0001555607,0.00001292369,0.00001209341,0.0003540994,0.00002770376,0.0004265876],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6094883,"threshold_uncertainty_score":0.5999326,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01290414808912813,"score_gpt":0.2501768729611659,"score_spread":0.2372727248720377,"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."}}