{"id":"W3121540328","doi":"10.17504/protocols.io.bpegmjbw","title":"McGill Nanopore Ligation LibPrep Protocol SQK-LSK109 v1","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Nanopore; Amplicon; Fragmentation (computing); Ligation; Nanopore sequencing; DNA fragmentation; Sequencing by ligation; DNA; Computer science; Computational biology; Biology; Molecular biology; Nanotechnology; Genetics; Genomic library; Materials science; Polymerase chain reaction; DNA sequencing; Gene; Programming language; Base sequence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001527686,0.00170194,0.001518283,0.00213722,0.001527052,0.001681937,0.002436731,0.001334388,0.05745732],"category_scores_gemma":[0.002350076,0.001875564,0.0009508604,0.001376219,0.000832043,0.000965599,0.001937302,0.003442209,0.07733072],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009612518,"about_ca_system_score_gemma":0.001930126,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003169632,"about_ca_topic_score_gemma":0.007781092,"domain_scores_codex":[0.9975884,0.0003576811,0.0001911084,0.0005863864,0.000974133,0.000302362],"domain_scores_gemma":[0.9989858,0.0001822804,0.00006901706,0.0004223987,0.0002221453,0.000118294],"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":[0.0004132716,0.0001094196,0.000616103,0.001246847,0.00008939075,0.0003114217,0.0002567827,0.0004275059,0.7450225,0.00822166,0.180471,0.06281415],"study_design_scores_gemma":[0.00005881055,0.0001050261,0.001395881,0.00008504275,0.0000649323,0.0008839488,0.00003478779,0.001422805,0.3823972,0.002836295,0.6105973,0.0001179393],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"protocol","genre_scores_codex":[0.02721439,0.005299304,0.7150488,0.00212978,0.002182578,0.003850063,0.09398183,0.06777224,0.08252094],"genre_scores_gemma":[0.0454647,0.00299919,0.5108445,0.001965272,0.0003673097,0.005603833,0.2510435,0.02144259,0.1602691],"genre_candidate":"protocol","genre_consensus":null,"teacher_disagreement_score":0.05745732,"threshold_uncertainty_score":0.1922139,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02114744013542696,"score_gpt":0.3169519288981233,"score_spread":0.2958044887626963,"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."}}