{"id":"W2106808791","doi":"10.1093/bioinformatics/btn565","title":"Slider—maximum use of probability information for alignment of short sequence reads and SNP detection","year":2008,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":59,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University; BC Cancer Agency","funders":"Michael Smith Health Research BC","keywords":"Computer science; Sequence (biology); Base (topology); Algorithm; SNP; Slider; Data mining; Mathematics; Genetics; Engineering; Single-nucleotide polymorphism","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":[],"consensus_categories":[],"category_scores_codex":[0.0001214837,0.0000839212,0.0001265056,0.00002884994,0.00005330584,0.000005774777,0.0000506488,0.00007121635,3.986519e-7],"category_scores_gemma":[0.00009648933,0.00007556101,0.00004576349,0.00003731205,0.0001107557,0.000008359315,0.00005889277,0.00001811074,2.372095e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009601854,"about_ca_system_score_gemma":0.00003752418,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001606689,"about_ca_topic_score_gemma":0.000009081572,"domain_scores_codex":[0.9993693,0.000007463722,0.0003835019,0.00006049811,0.00008119515,0.00009808587],"domain_scores_gemma":[0.9994703,0.00001626278,0.0001429851,0.0001766542,0.0001654075,0.00002841654],"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":[0.0003309174,0.0001095996,0.02986752,0.001229918,0.0002253112,1.556477e-7,0.003306953,0.0009551921,0.9001717,0.0003664308,0.0006342402,0.06280207],"study_design_scores_gemma":[0.0005934885,0.001040046,0.02609669,0.00002337149,0.00004647255,0.00002973987,0.0003411435,0.005013198,0.9488408,0.0004507858,0.01727382,0.0002504628],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9797279,0.00006408642,0.01955943,0.00001130612,0.0000510814,0.0003826079,0.0000983673,0.000002025596,0.0001032526],"genre_scores_gemma":[0.9706337,0.000368732,0.02887475,0.00003585073,0.00001328484,0.00002148147,0.00004046353,0.000003453036,0.000008269975],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0625516,"threshold_uncertainty_score":0.3081289,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06261196664988462,"score_gpt":0.2598128996073277,"score_spread":0.1972009329574431,"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."}}