{"id":"W4391432517","doi":"10.1007/978-3-031-52730-2_9","title":"Untethered Robotic Manipulation of Reproductive Cells","year":2023,"lang":"en","type":"book-chapter","venue":"","topic":"Microfluidic and Bio-sensing Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Human–computer interaction","routes":{"ca_aff":true,"ca_fund":false,"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":[0.00006343288,0.0001861746,0.0002671684,0.0001497468,0.00001266017,0.00000558878,0.0001071513,0.0003327216,0.000115273],"category_scores_gemma":[0.00001132895,0.0001691283,0.00007567448,0.00003617724,0.0000639827,0.00001921074,0.00005124326,0.0001789744,0.0002580674],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004163802,"about_ca_system_score_gemma":0.000006810271,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000127626,"about_ca_topic_score_gemma":0.000004867651,"domain_scores_codex":[0.9993291,0.000002150946,0.0002365068,0.0002229236,0.0001002241,0.0001090466],"domain_scores_gemma":[0.9994252,0.0000230439,0.00005497025,0.0004395951,0.00004553239,0.00001162478],"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":[0.00002085561,0.00001712568,0.000008704381,0.001015652,0.0006890812,0.00006400097,0.0002347271,0.01394395,0.4972453,0.2366387,0.2195094,0.03061255],"study_design_scores_gemma":[0.0002068719,0.00009074955,0.00005443025,0.0006291753,0.0001829168,0.00001366872,0.0001280053,0.004253096,0.867665,0.08650191,0.03928461,0.0009895663],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0003718979,0.001611869,0.01432729,0.0001295718,0.001642299,0.00047265,0.00002627137,0.00480391,0.9766142],"genre_scores_gemma":[0.05451886,0.001651531,0.002264533,0.000006054068,0.0001224031,0.000001388505,0.00003893784,0.000138492,0.9412578],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.3704197,"threshold_uncertainty_score":0.6896853,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03466559844614612,"score_gpt":0.2042752751386703,"score_spread":0.1696096766925242,"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."}}