{"id":"W2140154634","doi":"10.1093/bioinformatics/btr046","title":"SHRiMP2: Sensitive yet Practical Short Read Mapping","year":2011,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":365,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Canadian Institutes of Health Research","keywords":"Executable; Computer science; Shrimp; Space (punctuation); Sensitivity (control systems); Source code; Code (set theory); Data mining; Programming language; Biology; Operating system; Engineering; Set (abstract data type)","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001565957,0.0001445522,0.0001329408,0.00003284373,0.00008388453,0.00001611235,0.00009326126,0.0001135351,0.00001532911],"category_scores_gemma":[0.00009087575,0.0001303471,0.00006876078,0.00005402002,0.00008217278,0.000002093192,0.0001670863,0.00007029137,0.00005115902],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008981299,"about_ca_system_score_gemma":0.00005946942,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000924592,"about_ca_topic_score_gemma":0.000007701881,"domain_scores_codex":[0.9992459,0.00001736437,0.0002623703,0.000134419,0.00009653297,0.0002434328],"domain_scores_gemma":[0.9994694,0.00001321922,0.00006625839,0.0002800105,0.00009109812,0.00008003413],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0008081504,0.0009293281,0.04237609,0.000512736,0.002693739,0.0001332313,0.03653371,0.00004487654,0.6844125,0.01243056,0.09276902,0.1263561],"study_design_scores_gemma":[0.001665206,0.001791227,0.1170001,0.0000992282,0.0002369154,0.0006885375,0.01656009,0.00365515,0.4085402,0.001006901,0.4464517,0.002304693],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8718505,0.0001843853,0.01134682,0.0001088044,0.0004380447,0.0003117165,0.0000526998,0.00001635429,0.1156907],"genre_scores_gemma":[0.9292775,0.0002460259,0.0695459,0.0004718759,0.0001199283,0.00000925669,0.00003949834,0.00001592166,0.0002741126],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3536827,"threshold_uncertainty_score":0.53154,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0499284744864106,"score_gpt":0.2654698643525903,"score_spread":0.2155413898661797,"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."}}