{"id":"W2269578307","doi":"10.1101/032110","title":"Centromere Detection of Human Metaphase Chromosome Images using a Candidate Based Method","year":2015,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Genomic variations and chromosomal abnormalities","field":"Biochemistry, Genetics and Molecular Biology","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Nuclear Laboratories; Western University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Centromere; Sister chromatids; Chromosome; Metaphase; Chromatid; Karyotype; Biology; Genetics; Pattern recognition (psychology); Computer science; Artificial intelligence; Gene","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":[0.0006195026,0.0004544589,0.0005390124,0.0002033324,0.0001565234,0.00008736941,0.0003834385,0.0004821434,0.00003178607],"category_scores_gemma":[0.00009210891,0.0004955044,0.0002309099,0.0002081243,0.0001025604,0.00001231844,0.0003687626,0.0002849874,0.000003634536],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001584823,"about_ca_system_score_gemma":0.0007819405,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004567557,"about_ca_topic_score_gemma":0.00001217217,"domain_scores_codex":[0.9977892,0.0002614013,0.0005599977,0.0007365872,0.0002507416,0.0004020469],"domain_scores_gemma":[0.9974951,0.00001143857,0.0005966564,0.001037689,0.000655119,0.0002039707],"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":[0.00003925214,0.0001100876,0.0007255854,0.0002519311,0.0002374576,0.000008733507,0.000005895323,0.0007003001,0.9978479,0.00003473487,0.00003629602,0.000001818839],"study_design_scores_gemma":[0.0007553473,0.000147344,0.003391152,0.00009192577,0.0002723428,7.609686e-8,0.000006701309,0.0007598601,0.9932355,0.000003454792,0.0008199016,0.0005163961],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9739193,0.001203538,0.02304121,0.00001950537,0.0004269934,0.0004067028,0.0009227748,0.00005185459,0.000008083788],"genre_scores_gemma":[0.983637,0.00004098135,0.01571231,0.00004313703,0.0003940273,0.00006503167,0.000007052,0.00009268385,0.000007718616],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009717725,"threshold_uncertainty_score":0.9997497,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01650560794860129,"score_gpt":0.255329199588168,"score_spread":0.2388235916395667,"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."}}