{"id":"W2966305019","doi":"10.1101/718973","title":"Automated Cytogenetic Biodosimetry at Population-Scale","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Carcinogens and Genotoxicity Assessment","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University; Canadian Nuclear Laboratories; Health Canada; Cytodiagnostics (Canada); Western University","funders":"Natural Sciences and Engineering Research Council of Canada; International Atomic Energy Agency; Ontario Centres of Excellence","keywords":"Biodosimetry; Dicentric chromosome; Metaphase; Population; Triage; Computer science; Nuclear medicine; Ionizing radiation; Chromosome; Biology; Medicine; Physics; Genetics; Irradiation","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001146596,0.0003972953,0.0003850273,0.001578965,0.0002697776,0.0009994998,0.0006058282,0.0002235122,0.005496886],"category_scores_gemma":[0.002400487,0.0002575935,0.0002136096,0.001214621,0.0002603735,0.0004155932,0.0006992622,0.0002905667,0.00130712],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006361958,"about_ca_system_score_gemma":0.0005035352,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004096938,"about_ca_topic_score_gemma":0.004638584,"domain_scores_codex":[0.999002,0.0001364888,0.00005134007,0.0003347921,0.0004179951,0.00005741596],"domain_scores_gemma":[0.9981183,0.0004680562,0.0002928369,0.0003107091,0.0007528161,0.00005733897],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0007789448,0.0001417835,0.2883979,0.0002587181,0.0001355435,0.0002007141,0.0005197915,0.02547075,0.3170559,0.001830805,0.004348585,0.3608606],"study_design_scores_gemma":[0.00006827124,0.0004576967,0.4890027,0.00007104911,0.000120375,0.0008268542,0.0004050954,0.1709153,0.317478,0.003218475,0.0173476,0.00008848548],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7010576,0.000597593,0.275411,0.0001510373,0.00004215748,0.0003236668,0.004469075,0.006646321,0.01130165],"genre_scores_gemma":[0.8169532,0.0002531639,0.1750742,0.00006553344,0.00003445971,0.0003098119,0.003006896,0.0002279741,0.004074766],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005496886,"threshold_uncertainty_score":0.01838893,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009285491646957338,"score_gpt":0.2339664091170303,"score_spread":0.224680917470073,"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."}}