{"id":"W2164755577","doi":"10.1117/1.3544543","title":"Detecting cell death with optical coherence tomography and envelope statistics","year":2011,"lang":"en","type":"article","venue":"Journal of Biomedical Optics","topic":"Optical Coherence Tomography Applications","field":"Engineering","cited_by":41,"is_retracted":false,"has_abstract":true,"ca_institutions":"Sunnybrook Health Science Centre; University of Toronto","funders":"Canadian Institutes of Health Research; Terry Fox Foundation; Canada Research Chairs; Cancer Care Ontario; American Institute of Ultrasound in Medicine","keywords":"Optical coherence tomography; Programmed cell death; Envelope (radar); Backscatter (email); In vivo; Biomedical engineering; Pathology; Single-cell analysis; Medicine; Apoptosis; Cell; Biology; Radiology; Computer science","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":[0.0002588471,0.0001795935,0.0002761098,0.0002316105,0.00005820659,0.00004107252,0.0002352247,0.000128991,0.00006006613],"category_scores_gemma":[0.00006122843,0.0001370479,0.0000525231,0.0004849095,0.0003491741,0.0001280582,0.00003490141,0.0005159972,0.000006501608],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002204245,"about_ca_system_score_gemma":0.00006390106,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000239995,"about_ca_topic_score_gemma":0.000002175069,"domain_scores_codex":[0.9986321,0.0000171747,0.0005067328,0.0001257523,0.0004117207,0.0003065026],"domain_scores_gemma":[0.9988207,0.0002118588,0.0001250762,0.0001545968,0.0001912198,0.0004965462],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001275579,0.005899488,0.1415416,0.003407151,0.003625742,0.004249267,0.01059101,0.0009239102,0.1167351,0.1204251,0.00519106,0.586135],"study_design_scores_gemma":[0.02060795,0.03346077,0.4786558,0.002843704,0.00514132,0.008640401,0.007259833,0.1390591,0.2095793,0.06948023,0.01627162,0.008999887],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4668454,0.000321178,0.5257896,0.00004694483,0.0001806975,0.0001735313,0.00003073763,0.00008922401,0.006522679],"genre_scores_gemma":[0.615739,0.00008725134,0.3840806,0.00001594599,0.00005019735,0.000003431059,0.000001216837,0.00001828838,0.000004101013],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5771351,"threshold_uncertainty_score":0.558865,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01630812739550681,"score_gpt":0.2183813922713783,"score_spread":0.2020732648758715,"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."}}