{"id":"W4362696199","doi":"10.1016/j.pacs.2023.100487","title":"Detection of clot formation & lysis In-Vitro using high frequency photoacoustic imaging & frequency analysis","year":2023,"lang":"en","type":"article","venue":"Photoacoustics","topic":"Photoacoustic and Ultrasonic Imaging","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Toronto Metropolitan University; SickKids Foundation; St. Michael's Hospital","funders":"Natural Sciences and Engineering Research Council of Canada; Tokyo Metropolitan University; Ontario Ministry of Research, Innovation and Science; Canadian Hematology Society; Canada Foundation for Innovation; Ryerson University","keywords":"Fibrinolysis; Whole blood; Medicine; Blood clotting; Clotting time; Lysis; Coagulation; Biomedical engineering; Internal medicine; Immunology","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006447748,0.0004773591,0.0007775548,0.002157787,0.0001745129,0.00007942491,0.0003413717,0.0001746164,0.00007767178],"category_scores_gemma":[0.0003607876,0.0005507978,0.0003075349,0.005378729,0.0001122478,0.0005024014,0.00006213573,0.0004902576,0.00006026882],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006615893,"about_ca_system_score_gemma":0.00007086562,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00175583,"about_ca_topic_score_gemma":0.0004079355,"domain_scores_codex":[0.9968141,0.00008044371,0.00111471,0.0004661868,0.000604464,0.0009201054],"domain_scores_gemma":[0.9983191,0.00033669,0.0002533366,0.0006979237,0.0002310031,0.0001619089],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001122256,0.00003048048,0.001053684,0.0002391284,0.0001888832,0.00001458961,0.0004816139,0.3217542,0.6756008,0.000005255543,0.00002768854,0.0005924671],"study_design_scores_gemma":[0.0004974329,0.00000672442,0.001849821,0.00007723198,0.001390598,0.00002896681,0.0003671846,0.8773268,0.11714,0.0007387489,0.00002755646,0.0005489116],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5530009,0.0001866856,0.4448946,0.000005768978,0.0004889143,0.0002529553,0.0002496173,0.0006704823,0.0002501378],"genre_scores_gemma":[0.9869506,0.0001993795,0.01216294,0.0000337762,0.0001163486,0.00005787266,0.0003110986,0.0001397874,0.00002817403],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5584608,"threshold_uncertainty_score":0.9996943,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0173883054099687,"score_gpt":0.241870846717297,"score_spread":0.2244825413073283,"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."}}