{"id":"W4310193714","doi":"10.1101/2022.11.23.517318","title":"Transformer-based spatial-temporal detection of apoptotic cell death in live-cell imaging","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Cell Image Analysis Techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Apoptosis; Intravital microscopy; In vivo; Programmed cell death; Robustness (evolution); Live cell imaging; Cell; Computer science; Artificial intelligence; Biomedical engineering; Biology; Medicine","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006313909,0.000505517,0.0005516007,0.0004447898,0.00008393193,0.00005676469,0.0005631307,0.0003608252,0.00007936834],"category_scores_gemma":[0.00005238751,0.0006227749,0.0003531086,0.0003538516,0.00008631077,0.000010632,0.0002643637,0.0006302475,0.00000520799],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001866166,"about_ca_system_score_gemma":0.0005214201,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001153742,"about_ca_topic_score_gemma":0.00008622322,"domain_scores_codex":[0.9972564,0.000229189,0.000703549,0.001037797,0.0003317105,0.0004413433],"domain_scores_gemma":[0.9979023,0.00001971063,0.0005069587,0.001204319,0.0002437266,0.0001229274],"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":[0.0000649833,0.0003287526,0.02681804,0.0004103473,0.00003666546,0.00002447211,0.00000525735,0.000284162,0.9719901,8.049757e-7,0.00002911323,0.000007307203],"study_design_scores_gemma":[0.0005995336,0.000142733,0.01058873,0.00007232484,0.0001321841,1.00034e-8,0.000005752706,0.001419715,0.9851813,6.407161e-7,0.001272324,0.0005847368],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9651925,0.001207242,0.03257414,0.0000197349,0.000128834,0.000660681,0.00006229522,0.0000969195,0.00005765628],"genre_scores_gemma":[0.9959043,0.0002554939,0.00326552,0.00008294507,0.0001149002,0.0002308209,0.00000708295,0.0001302472,0.000008685914],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0307118,"threshold_uncertainty_score":0.9996223,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006705581278843097,"score_gpt":0.2161846890547487,"score_spread":0.2094791077759056,"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."}}