{"id":"W1576253662","doi":"10.1002/cyto.a.22698","title":"Classification of blood cells and tumor cells using label‐free ultrasound and photoacoustics","year":2015,"lang":"en","type":"article","venue":"Cytometry Part A","topic":"Photoacoustic and Ultrasonic Imaging","field":"Engineering","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada; Ontario Ministry of Research, Innovation and Science; Canada Excellence Research Chairs, Government of Canada; Canada Foundation for Innovation; Canadian Cancer Society; Ryerson University","keywords":"Photoacoustic Doppler effect; Ultrasound; Photoacoustic imaging in biomedicine; Photoacoustic effect; SIGNAL (programming language); Materials science; Ultrasonic sensor; Melanoma; Absorption (acoustics); Microscope; Biomedical engineering; Optics; Pathology; Medicine; Acoustics; Physics; Computer science; Cancer research","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":[],"consensus_categories":[],"category_scores_codex":[0.0002487225,0.0001684891,0.0002407825,0.000154932,0.00004373182,0.0000440359,0.0001145213,0.00006567709,0.00001181379],"category_scores_gemma":[0.0001360281,0.0001766668,0.00001964362,0.0003212501,0.0001261163,0.0001220055,0.00003924592,0.0001450016,0.000003438498],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003461592,"about_ca_system_score_gemma":0.00003824345,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001277289,"about_ca_topic_score_gemma":0.000001127111,"domain_scores_codex":[0.9990868,0.0000187824,0.0002558975,0.0001936684,0.0001878625,0.0002569827],"domain_scores_gemma":[0.9992366,0.0001802079,0.00006556325,0.0002716631,0.00007073437,0.0001752042],"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":[0.000006056542,0.00004043381,0.002325925,0.0001650928,0.0000458017,0.000007619098,0.0002708604,0.0009370976,0.995022,0.00001712306,0.001050336,0.0001116372],"study_design_scores_gemma":[0.002003704,0.00007730072,0.002140462,0.0001329703,0.0004433019,0.0001940864,0.001193008,0.2459081,0.7461331,0.0002155842,0.001069381,0.0004890267],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9900412,0.0009877684,0.007360462,0.00000345714,0.0003596906,0.0001447316,0.000153149,0.00009600423,0.0008535314],"genre_scores_gemma":[0.9931132,0.0001099379,0.006579795,0.00002798052,0.00008364762,0.000004416182,0.000006077283,0.00003449299,0.00004046668],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2488889,"threshold_uncertainty_score":0.7204264,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03163642958651679,"score_gpt":0.2413074029206665,"score_spread":0.2096709733341497,"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."}}