{"id":"W2169437479","doi":"10.1109/coase.2010.5584613","title":"Detection and tracking of low contrast human sperm tail","year":2010,"lang":"en","type":"article","venue":"","topic":"Sperm and Testicular Function","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Sperm; Tracking (education); Sperm motility; Computer science; Algorithm; Computer vision; Intracytoplasmic sperm injection; Artificial intelligence; Biology; Biological system; In vitro fertilisation; Cell biology; Genetics; Embryo","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002990074,0.0001727632,0.0001723931,0.0005130842,0.0001293588,0.0003610247,0.0002998733,0.0005446287,0.0008660529],"category_scores_gemma":[0.0009842996,0.0001846379,0.000148359,0.0002260254,0.0001694025,0.0003257077,0.0002512689,0.0001720611,0.0004032337],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002093515,"about_ca_system_score_gemma":0.0002659396,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005814487,"about_ca_topic_score_gemma":0.0006819775,"domain_scores_codex":[0.9998807,0.00002033815,0.000005552733,0.00002804109,0.00005069424,0.00001469478],"domain_scores_gemma":[0.9997553,0.00009906098,0.00004652282,0.0000186668,0.00006743374,0.00001295403],"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":[0.0002788944,0.00003660078,0.006894216,0.0001527973,0.00001809485,0.0001761085,0.00009650574,0.005660321,0.7979045,0.001321653,0.000881351,0.186579],"study_design_scores_gemma":[0.00003458885,0.000475871,0.02246626,0.00004296523,0.00005217265,0.002436911,0.00008736033,0.2060103,0.759498,0.0009993647,0.007837437,0.00005884777],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.260254,0.001423069,0.7334969,0.0002027626,0.00005726824,0.00006834594,0.0001287445,0.001202521,0.003166407],"genre_scores_gemma":[0.647208,0.0009222866,0.3464152,0.0001655746,0.00003495489,0.00006554017,0.0002120199,0.00009766156,0.004878812],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0008660529,"threshold_uncertainty_score":0.002897263,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01183755725706964,"score_gpt":0.2472045326048864,"score_spread":0.2353669753478167,"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."}}