{"id":"W4391432423","doi":"10.1007/978-3-031-52730-2_4","title":"Automated Picoliter-Resolution Sperm Aspiration","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":"Sperm; Resolution (logic); Computer science; Medicine; Artificial intelligence; Andrology","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00005674524,0.0002530396,0.0002115401,0.0002202693,0.00004054969,0.00003968697,0.00011695,0.0006302344,0.0001775451],"category_scores_gemma":[0.00001015356,0.0002354164,0.00007659876,0.00004443746,0.0000500129,0.00004375554,0.00005744952,0.0002308799,0.001638821],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001133246,"about_ca_system_score_gemma":0.00001235041,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008475249,"about_ca_topic_score_gemma":0.00001357648,"domain_scores_codex":[0.9992319,0.000001852716,0.000243337,0.0001996637,0.0001301892,0.0001930992],"domain_scores_gemma":[0.9995953,0.00001443555,0.00003347738,0.0002937661,0.00003680907,0.00002617982],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000004578558,0.000006157489,0.00000279759,0.0002072386,0.0001329119,0.0000634574,0.00003842304,0.0002797106,0.0408057,0.1559912,0.7638487,0.03861921],"study_design_scores_gemma":[0.0002344037,0.0001065668,0.0001087955,0.0003986685,0.00008242169,0.00002924552,0.00001646926,0.07928745,0.01012477,0.01475751,0.8938164,0.001037308],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0003850468,0.0007850017,0.002978376,0.0001434889,0.001031155,0.0002966979,0.00004839935,0.04584563,0.9484862],"genre_scores_gemma":[0.0133035,0.001017976,0.001202447,0.00006980222,0.0002436058,0.000005915964,0.0003229546,0.0001827544,0.983651],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.1412336,"threshold_uncertainty_score":0.9991385,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02600511355625021,"score_gpt":0.2123309496892581,"score_spread":0.1863258361330078,"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."}}