{"id":"W2127171250","doi":"10.1002/047001153x.g401105","title":"Contig mapping and analysis","year":2005,"lang":"en","type":"other","venue":"Encyclopedia of Genetics, Genomics, Proteomics and Bioinformatics","topic":"Genomics and Chromatin Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"BC Cancer Agency","funders":"BC Cancer Foundation","keywords":"Contig; Section (typography); Set (abstract data type); Computer science; Path (computing); Fingerprint (computing); Computational biology; Artificial intelligence; Biology; Genetics; Genome; Programming language","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":[0.0002716863,0.0005504995,0.0008132668,0.0004678525,0.00007820012,0.00007090942,0.0003572242,0.0006849297,0.00006616941],"category_scores_gemma":[0.00003643391,0.0005734814,0.000214738,0.0001637539,0.0003187041,0.000005075703,0.0005305279,0.0001993303,0.000007701982],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002813675,"about_ca_system_score_gemma":0.0001597821,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004674169,"about_ca_topic_score_gemma":0.0002447231,"domain_scores_codex":[0.9979504,0.00002998392,0.0009320879,0.0004928211,0.0001780693,0.0004166696],"domain_scores_gemma":[0.9980592,0.00001218428,0.0009234683,0.0007097274,0.00008644148,0.0002090478],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004845232,0.001181881,0.0790368,0.01180711,0.03271234,0.00002501906,0.01019893,0.003712839,0.07558554,0.001688439,0.2704628,0.5131037],"study_design_scores_gemma":[0.001325788,0.000351552,0.00241916,0.0001119762,0.001038778,0.00002541959,0.0004987395,0.01917475,0.001557626,0.0001301517,0.9718478,0.001518218],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.5045495,0.04873832,0.04586854,0.0002856438,0.001112506,0.00453981,0.003735068,0.0001317437,0.3910389],"genre_scores_gemma":[0.007256155,0.2880765,0.5533898,0.0003959848,0.001523871,0.00006817411,0.002119023,0.0007810153,0.1463895],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.701385,"threshold_uncertainty_score":0.9996716,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00428470329755984,"score_gpt":0.198300702993451,"score_spread":0.1940159996958911,"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."}}