{"id":"W4243471698","doi":"10.32920/14639112","title":"Seeds for effective oligonucleotide design","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Oligonucleotide; Seeding; Computer science; Algorithm; Measure (data warehouse); Data mining; Biology; DNA; Agronomy; Genetics","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":[0.00239495,0.001077878,0.001058478,0.001231636,0.0008167194,0.001547722,0.001097641,0.00180279,0.007538402],"category_scores_gemma":[0.01423878,0.0008493509,0.0008619221,0.0009267503,0.002055295,0.001599458,0.001485105,0.001451069,0.003081509],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009461836,"about_ca_system_score_gemma":0.001161405,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004117927,"about_ca_topic_score_gemma":0.0004161387,"domain_scores_codex":[0.9970988,0.0009954402,0.0002091988,0.0005504719,0.0009899285,0.00015618],"domain_scores_gemma":[0.9922653,0.004588324,0.0006782712,0.001174032,0.001014031,0.0002800178],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0006039998,0.0001865837,0.002177773,0.001369402,0.0000845402,0.0004944864,0.0004388017,0.2469052,0.08176336,0.368912,0.01024445,0.2868194],"study_design_scores_gemma":[0.000166382,0.0004531082,0.0003256695,0.0002038947,0.00005032857,0.0005265411,0.00007802703,0.5104603,0.0502978,0.3967799,0.04059646,0.00006159498],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01228832,0.000748138,0.9798371,0.0002467013,0.0001384239,0.0001360091,0.000132005,0.001180381,0.005292964],"genre_scores_gemma":[0.1591543,0.0005744869,0.8350642,0.0002638907,0.00008032984,0.0003768867,0.0003506078,0.0005956147,0.003539708],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007538402,"threshold_uncertainty_score":0.02521849,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0151250049932661,"score_gpt":0.293788518869194,"score_spread":0.278663513875928,"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."}}