{"id":"W4403905440","doi":"10.1016/j.optlastec.2024.111992","title":"Automated cell profiling in imaging flow cytometry with annotation-efficient learning","year":2024,"lang":"en","type":"article","venue":"Optics & Laser Technology","topic":"Cell Image Analysis Techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"","keywords":"Profiling (computer programming); Annotation; Computer science; Flow cytometry; Artificial intelligence; Computational biology; Biology; Molecular biology; Programming language","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":[0.001695374,0.000890105,0.001223506,0.001257524,0.0008495888,0.001860223,0.002557693,0.001349168,0.002602042],"category_scores_gemma":[0.003339723,0.0007126222,0.0008623506,0.001805541,0.0007732154,0.001792559,0.001791596,0.00154571,0.002215415],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001297282,"about_ca_system_score_gemma":0.002256198,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004431707,"about_ca_topic_score_gemma":0.006819687,"domain_scores_codex":[0.9987891,0.0002748974,0.00008104206,0.0003258395,0.000383547,0.0001456101],"domain_scores_gemma":[0.998198,0.0007399895,0.0001595907,0.0004651847,0.0003751427,0.00006215324],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003819059,0.0002773654,0.00268379,0.0002696174,0.00007186367,0.00007267085,0.0001869182,0.06629372,0.148798,0.01195265,0.004595414,0.7644161],"study_design_scores_gemma":[0.00001712744,0.00006095318,0.001480425,0.00002252233,0.00002211558,0.00009614637,0.00004183753,0.8769612,0.1036511,0.01259599,0.005013382,0.00003726657],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009825618,0.000097558,0.9854359,0.00008527454,0.00001410753,0.00006373035,0.0002129382,0.003826248,0.0004386319],"genre_scores_gemma":[0.1087677,0.0001747005,0.8877715,0.0000991924,0.00002253801,0.0003227542,0.0008549953,0.0003548329,0.001631696],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004431707,"threshold_uncertainty_score":0.009412467,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002453496621141583,"score_gpt":0.2406983113452087,"score_spread":0.2382448147240672,"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."}}