{"id":"W4412163819","doi":"10.1158/1557-3265.aimachine-b052","title":"Abstract B052: Utilizing Dimensionality Reduction for Classification of Cell Senescence and Immune Synapse Formation via Imaging Flow Cytometry","year":2025,"lang":"en","type":"article","venue":"Clinical Cancer Research","topic":"Advanced Biosensing Techniques and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Senescence; Flow cytometry; Cellular senescence; Immune system; Immunological synapse; Cell biology; Cell; Biology; Chemistry; Neuroscience; Immunology; T cell; Biochemistry; Phenotype","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002029831,0.0009715604,0.00105471,0.002290227,0.0005733966,0.00176969,0.0008322404,0.001140193,0.001679056],"category_scores_gemma":[0.003682125,0.00023279,0.001361337,0.001465514,0.0003599402,0.0006099819,0.0007771853,0.0009683814,0.001452982],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007850152,"about_ca_system_score_gemma":0.001142801,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00310508,"about_ca_topic_score_gemma":0.0018179,"domain_scores_codex":[0.9987766,0.0002650825,0.0001163744,0.0003161661,0.0003682971,0.0001575267],"domain_scores_gemma":[0.9988388,0.000277006,0.0001213112,0.0001739485,0.0005146459,0.00007424714],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0009775297,0.0007674969,0.02467505,0.0003834819,0.0003814608,0.000288631,0.0003422159,0.07618718,0.2212215,0.00512068,0.0197731,0.6498817],"study_design_scores_gemma":[0.00003726673,0.0001743233,0.01346758,0.00002262859,0.00004737294,0.0001603854,0.00008785886,0.9350211,0.04198997,0.004004206,0.004928455,0.00005882763],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2475171,0.0008746059,0.7366018,0.0008763388,0.0002374298,0.0005272059,0.004215313,0.006632624,0.002517551],"genre_scores_gemma":[0.467926,0.0004561185,0.5140606,0.0002592174,0.0001436577,0.0008687259,0.01275307,0.0002449335,0.003287713],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00310508,"threshold_uncertainty_score":0.01073492,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1089998548303821,"score_gpt":0.4973195803481481,"score_spread":0.388319725517766,"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."}}