{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001616328,0.0005148978,0.0006284614,0.0001722369,0.0003016455,0.0002130358,0.0006100775,0.0002555962,0.0005797529],"category_scores_gemma":[0.000008756722,0.000659833,0.0004732079,0.0004118977,0.0001013754,0.0002048449,0.0009692312,0.0009614588,0.00004508316],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005423997,"about_ca_system_score_gemma":0.001417767,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001765221,"about_ca_topic_score_gemma":0.00005458234,"domain_scores_codex":[0.9976351,0.0001670658,0.0003140137,0.001104837,0.00006641774,0.0007125686],"domain_scores_gemma":[0.9983585,0.00007701927,0.0003916782,0.0008179814,0.0001753062,0.000179524],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004371298,0.0003134292,0.01192926,0.0002019181,0.0009047248,0.0002941498,0.0003030299,0.9518585,0.0176608,0.0151746,0.0001391356,0.001176783],"study_design_scores_gemma":[0.004460935,0.0001375864,0.00124432,0.001378657,0.002331616,0.00003522518,0.001469145,0.9428943,0.02699486,0.01397106,0.0009447263,0.00413752],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.784821,0.0003181998,0.2114653,0.000008688848,0.0004225025,0.0002739808,0.00003237584,0.00009821652,0.002559723],"genre_scores_gemma":[0.993515,0.00002881616,0.002710408,0.00002241376,0.0003191855,7.440436e-7,0.0001789548,0.00006605324,0.003158401],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2087549,"threshold_uncertainty_score":0.9995853,"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."}}