{"id":"W2122324578","doi":"10.1109/ccece.2002.1013111","title":"Biological cell motion tracking in dielectrophoresis (DEP) levitation feedback control system","year":2003,"lang":"en","type":"article","venue":"","topic":"Microfluidic and Bio-sensing Technologies","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer vision; Artificial intelligence; Computer science; Initialization; Template matching; Dielectrophoresis; Tracking (education); Merge (version control); Frame (networking); Image (mathematics); Physics; Microfluidics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001509263,0.0001810921,0.0001574289,0.000187033,0.0002169824,0.0002068698,0.0003839689,0.0003269575,0.0005049112],"category_scores_gemma":[0.0002912664,0.0001310151,0.0001022631,0.00009518082,0.0002445362,0.0002824466,0.0002434347,0.000133257,0.0001320781],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003551859,"about_ca_system_score_gemma":0.0002344041,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001711325,"about_ca_topic_score_gemma":0.001992879,"domain_scores_codex":[0.9999123,0.00001008625,0.000004083983,0.00001942371,0.00004580062,0.000008394394],"domain_scores_gemma":[0.9998822,0.00005084543,0.00001519048,0.00001136928,0.00003065771,0.000009753045],"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":[0.0001411317,0.00003993311,0.001257772,0.00009912435,0.000009979052,0.0002216414,0.0001959515,0.08826016,0.7797758,0.003981087,0.0004539596,0.1255636],"study_design_scores_gemma":[0.00001570753,0.000143287,0.001726196,0.000006197812,0.000007480417,0.0001348425,0.00003850988,0.8319063,0.1617563,0.001344282,0.002906806,0.00001416615],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2019659,0.0002565234,0.7951471,0.0001502359,0.00004198113,0.00003628057,0.00003395375,0.0006267881,0.001741312],"genre_scores_gemma":[0.8096269,0.0001834731,0.1862805,0.00006182361,0.0000103507,0.00005706723,0.000053339,0.00002475376,0.003701926],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001711325,"threshold_uncertainty_score":0.00340271,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01167892223918373,"score_gpt":0.1882909454850635,"score_spread":0.1766120232458798,"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."}}