{"id":"W4229943617","doi":"10.32920/14637090","title":"Detecting apoptosis using dynamic light scattering with optical coherence tomography","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Optical Coherence Tomography Applications","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; Health Sciences Centre; Sunnybrook Health Science Centre; Toronto Metropolitan University; University of Toronto; Ontario Institute for Cancer Research","funders":"","keywords":"Optical coherence tomography; Intracellular; Coherence (philosophical gambling strategy); Frame rate; Apoptosis; Speckle pattern; Dynamic light scattering; Optics; Scattering; Physics; Chemistry; Biology; Cell biology; Biochemistry","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001390706,0.0006349341,0.0005935824,0.0003936152,0.0001573535,0.0004944688,0.000579059,0.0004481839,0.0001880378],"category_scores_gemma":[0.00001752148,0.0006248851,0.0002823286,0.001111143,0.0001513553,0.0001832986,0.0004843104,0.001339857,0.00001528695],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001682119,"about_ca_system_score_gemma":0.00009472514,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005811164,"about_ca_topic_score_gemma":0.0001396792,"domain_scores_codex":[0.9974779,0.00003127551,0.0005301093,0.0008582006,0.0004072048,0.0006952999],"domain_scores_gemma":[0.9982597,0.0001054518,0.00008617842,0.001092085,0.0001802264,0.0002763261],"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":[0.00002916911,0.0002890735,0.006116614,0.003106527,0.001843112,0.00005555498,0.0007362473,0.434094,0.525906,0.0009072965,0.00003851271,0.02687786],"study_design_scores_gemma":[0.0006212997,0.0001288532,0.004466722,0.003079867,0.0009306403,0.000125525,0.001397576,0.701851,0.2823645,0.0007277178,0.0001115576,0.004194751],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7608289,0.0003358285,0.2285226,0.00006802389,0.0002535517,0.0005866534,0.00001193859,0.001253907,0.008138683],"genre_scores_gemma":[0.8378742,0.00002789188,0.1615862,0.00002170354,0.00005325336,0.000280055,0.00002445253,0.000121011,0.00001117768],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.267757,"threshold_uncertainty_score":0.9996203,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01321244174429059,"score_gpt":0.2371393355333296,"score_spread":0.223926893789039,"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."}}