{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001364212,0.0003201725,0.0002340941,0.0002130401,0.0002158977,0.0004309207,0.0004004301,0.0003067235,0.001213607],"category_scores_gemma":[0.0002790422,0.0002905866,0.0001421766,0.000136847,0.0003709317,0.0006257745,0.0004667206,0.0003363626,0.0003412487],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002447872,"about_ca_system_score_gemma":0.0001358005,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001918298,"about_ca_topic_score_gemma":0.0004464237,"domain_scores_codex":[0.9998612,0.00001237349,0.000008898577,0.00004263666,0.00005215893,0.00002252864],"domain_scores_gemma":[0.9998921,0.00003814371,0.00002618538,0.00001651083,0.00001107245,0.00001591067],"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":[0.00006071673,0.00001620734,0.0001409308,0.00003622575,0.000004819944,0.0001060231,0.000058557,0.002450103,0.987227,0.00295249,0.0001496221,0.006797377],"study_design_scores_gemma":[0.00004384252,0.0001106533,0.0006700265,0.000008985796,0.000009061404,0.0001762562,0.00003759671,0.05727668,0.9322056,0.001052866,0.008377309,0.0000310026],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8397214,0.001594695,0.1448645,0.0004774644,0.0003530972,0.0001457753,0.0001924559,0.001801581,0.01084902],"genre_scores_gemma":[0.946822,0.0004170051,0.04914104,0.00006683581,0.00002347002,0.0000634387,0.00003510746,0.00006593449,0.003365195],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001213607,"threshold_uncertainty_score":0.004059911,"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."}}