{"id":"W4406345613","doi":"10.1109/tase.2025.3529283","title":"Automated Sperm Tracking and Immobilization With a Clinically-Compatible XYZ Stage","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Automation Science and Engineering","topic":"Reproductive Biology and Fertility","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Sperm; Computer science; Tracking (education); Engineering; Control engineering; Biomedical engineering; Medicine; Andrology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004888618,0.00008719538,0.0001363796,0.0002520333,0.0001837539,0.00003976742,0.00003587731,0.0000509773,0.000009932187],"category_scores_gemma":[0.00006204643,0.00006888738,0.0000146502,0.0006507104,0.0001951281,0.0002763796,0.000001076898,0.0001208269,0.000001625848],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005165563,"about_ca_system_score_gemma":0.0001009587,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006785563,"about_ca_topic_score_gemma":0.000001719289,"domain_scores_codex":[0.9992304,0.00001098537,0.0001883195,0.0002998137,0.0001427183,0.0001276992],"domain_scores_gemma":[0.9995557,0.00005722783,0.00002941686,0.0001500374,0.0001470232,0.00006061033],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002325749,0.0007679802,0.02096522,0.00104073,0.0002119031,0.00001500278,0.002998621,0.1112593,0.6424975,0.001073989,0.00003346195,0.2168105],"study_design_scores_gemma":[0.000534207,0.0002077432,0.4109921,0.0001296245,0.00003095284,0.00001232814,0.000106008,0.5596005,0.02822025,0.000007291794,0.00007501708,0.00008399854],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7014055,0.00001887756,0.2975988,0.0001829806,0.0001052797,0.0001838678,0.00000152383,0.000289846,0.0002133409],"genre_scores_gemma":[0.9978062,0.00003670101,0.001947213,0.00008806088,0.000007369924,0.00001589914,9.113247e-7,0.000004288081,0.00009338699],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6142772,"threshold_uncertainty_score":0.2809146,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01999016886517941,"score_gpt":0.3061266591517942,"score_spread":0.2861364902866148,"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."}}