{"id":"W4287279914","doi":"10.48550/arxiv.2103.04912","title":"Autonomous object harvesting using synchronized optoelectronic microrobots","year":2021,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Micro and Nano Robotics","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Engineering and Physical Sciences Research Council; Natural Sciences and Engineering Research Council of Canada; UK Research and Innovation","keywords":"Dielectrophoresis; Computer science; Nanotechnology; Artificial intelligence; Engineering; Materials science; Microfluidics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016346,0.0002516749,0.0003040603,0.0001816965,0.0002517447,0.0005684372,0.0004748916,0.0003303926,0.0005633654],"category_scores_gemma":[0.0003312477,0.0002540481,0.0002351796,0.0002449609,0.0003550234,0.0005698568,0.0006722657,0.0002165304,0.0001521778],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003867218,"about_ca_system_score_gemma":0.0003169792,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006520856,"about_ca_topic_score_gemma":0.0009498444,"domain_scores_codex":[0.9998333,0.00001987423,0.000008495688,0.00004725301,0.00006326475,0.00002771215],"domain_scores_gemma":[0.9998628,0.00005410293,0.000026023,0.0000239913,0.00001609181,0.00001697093],"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":[0.0001100014,0.00005394067,0.0006094767,0.00008013609,0.00002036438,0.0001574441,0.0001071401,0.04526689,0.9320683,0.004453483,0.0003106256,0.01676226],"study_design_scores_gemma":[0.00007771792,0.0002021818,0.001706393,0.00001152128,0.00002343475,0.00009228598,0.0000811375,0.5523729,0.43629,0.003481553,0.00560755,0.00005334047],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7105829,0.000638857,0.2831935,0.0001692576,0.0001194831,0.00008756512,0.0001192763,0.0007694014,0.004319706],"genre_scores_gemma":[0.9442348,0.0003598166,0.05345494,0.00005133309,0.00001804948,0.00007500419,0.00005747881,0.00004492235,0.001703661],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0006520856,"threshold_uncertainty_score":0.002805829,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0559583232769908,"score_gpt":0.1972297197159912,"score_spread":0.1412713964390004,"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."}}