{"id":"W4377086801","doi":"10.1093/bioinformatics/btad328","title":"GIL: a python package for designing custom indexing primers","year":2023,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Algorithms and Data Compression","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; University of British Columbia; Western Canada Research Grid; Stem Cell Network; Canadian Institutes of Health Research; Compute Canada","keywords":"Python (programming language); Search engine indexing; Programming language; Computer science; R package; Information retrieval","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":[0.003295685,0.00250256,0.001878864,0.001977601,0.001304763,0.002957051,0.003719976,0.00110119,0.1073815],"category_scores_gemma":[0.009848475,0.002474493,0.001922022,0.001772629,0.0009301091,0.002436275,0.003022265,0.003638427,0.08335165],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001150075,"about_ca_system_score_gemma":0.003038722,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002242972,"about_ca_topic_score_gemma":0.003449851,"domain_scores_codex":[0.9976471,0.0003665561,0.0003038431,0.0006995008,0.000701192,0.0002818111],"domain_scores_gemma":[0.997265,0.001294572,0.0002801746,0.0004997454,0.0004749397,0.0001855777],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00101522,0.0001792398,0.003328602,0.003674675,0.0003706663,0.000394847,0.0006104719,0.006038689,0.04110224,0.01379556,0.7296231,0.1998665],"study_design_scores_gemma":[0.0003919709,0.0001765015,0.003203345,0.0004543599,0.000177876,0.0007712606,0.0001616037,0.04582868,0.09035248,0.03811494,0.8199868,0.0003802164],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"software","genre_gemma":"software","genre_scores_codex":[0.002794089,0.0004591702,0.3870747,0.0003529647,0.0003748198,0.0005444239,0.07480764,0.5257096,0.007882605],"genre_scores_gemma":[0.02003827,0.0005799796,0.6616293,0.00186483,0.0001712163,0.003712727,0.1001327,0.1949673,0.01690364],"genre_candidate":"software","genre_consensus":"software","teacher_disagreement_score":0.1073815,"threshold_uncertainty_score":0.3592269,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03511654673081748,"score_gpt":0.2756738779568974,"score_spread":0.2405573312260799,"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."}}