{"id":"W2130654549","doi":"10.1186/1748-7188-8-20","title":"Fast half-sibling population reconstruction: theory and algorithms","year":2013,"lang":"en","type":"article","venue":"Algorithms for Molecular Biology","topic":"Genome Rearrangement Algorithms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Government of Ontario","keywords":"Kinship; Computer science; Heuristic; Population; Inference; Inheritance (genetic algorithm); Cluster analysis; Integer (computer science); Theoretical computer science; Data mining; Machine learning; Artificial intelligence; Biology; Demography","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":[0.0005171353,0.0003305934,0.0003128301,0.0001692177,0.0001884741,0.00006718929,0.000223492,0.0003790761,0.00006849908],"category_scores_gemma":[0.0001521316,0.0003230177,0.0001656175,0.0001547043,0.0001945081,0.00001719133,0.0001630711,0.0001262511,0.00002476147],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002493228,"about_ca_system_score_gemma":0.00003290236,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001186317,"about_ca_topic_score_gemma":0.000008980289,"domain_scores_codex":[0.9979895,0.0002024885,0.0003880019,0.0007818367,0.0001030152,0.0005351047],"domain_scores_gemma":[0.998984,0.00005146137,0.0001610706,0.0004334776,0.0002109994,0.0001589946],"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":[0.00005510568,0.00005411202,0.003069086,0.00003608563,0.0002963767,0.00000272659,0.00004312048,0.00003437902,0.5428882,0.004776669,0.0002293308,0.4485148],"study_design_scores_gemma":[0.01546735,0.007293237,0.0299427,0.0001762923,0.0007424832,0.00203783,0.002148576,0.0199335,0.5591962,0.2631418,0.09350741,0.006412616],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5255697,0.002673988,0.4683041,0.0005599441,0.0007998255,0.001448579,0.00005691278,0.00007147722,0.0005154723],"genre_scores_gemma":[0.7946932,0.0005288451,0.1984966,0.001061714,0.00100859,0.0009168734,0.001872418,0.000166457,0.001255219],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4421021,"threshold_uncertainty_score":0.9999222,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00999279403419891,"score_gpt":0.266749084789505,"score_spread":0.2567562907553061,"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."}}