{"id":"W2737931494","doi":"10.1186/s12920-017-0279-9","title":"Secure approximation of edit distance on genomic data","year":2017,"lang":"en","type":"article","venue":"BMC Medical Genomics","topic":"Genome Rearrangement Algorithms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":47,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada; Zayed University","keywords":"Edit distance; Plaintext; Computer science; Similarity (geometry); String (physics); Set (abstract data type); Intersection (aeronautics); Metric (unit); Sequence (biology); Algorithm; Domain (mathematical analysis); Approximation algorithm; Theoretical computer science; Artificial intelligence; Mathematics; Encryption; Image (mathematics); Biology","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":[0.001840458,0.0007002224,0.001435439,0.001794946,0.0006194203,0.001740308,0.002035721,0.001247535,0.001764301],"category_scores_gemma":[0.01607721,0.0003724912,0.0009117728,0.002670784,0.001020474,0.003819237,0.002375788,0.001804023,0.0005561371],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001887082,"about_ca_system_score_gemma":0.001535434,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00230212,"about_ca_topic_score_gemma":0.001726631,"domain_scores_codex":[0.9961183,0.000850322,0.0002981734,0.0008552712,0.001588168,0.0002898533],"domain_scores_gemma":[0.9861678,0.007643528,0.001172621,0.003685774,0.001072219,0.0002579452],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007937598,0.0001866591,0.003734849,0.0002864967,0.0001240589,0.0003138875,0.0003433085,0.6691738,0.008785359,0.05686778,0.003031005,0.2563589],"study_design_scores_gemma":[0.00002719377,0.00007985911,0.000406391,0.00001346987,0.00001476801,0.0001990969,0.00004989907,0.9484981,0.004506416,0.04492217,0.001271915,0.00001074186],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.06860594,0.0005544132,0.9271381,0.0003820433,0.00004513617,0.00008117408,0.0005035138,0.001600557,0.001089031],"genre_scores_gemma":[0.6239795,0.0003941075,0.3716559,0.0001520239,0.00009533723,0.0001742863,0.001702671,0.0001329332,0.001713313],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00230212,"threshold_uncertainty_score":0.01369178,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03924657293843731,"score_gpt":0.2989500247440331,"score_spread":0.2597034518055958,"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."}}