{"id":"W4361857304","doi":"10.17504/protocols.io.n2bvj8oowgk5/v1","title":"HTTM : Illumina libraries v1","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Environmental DNA in Biodiversity Studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Illumina dye sequencing; Computational biology; Information retrieval; Biology; Computer science; Genetics; DNA sequencing; Gene","routes":{"ca_aff":true,"ca_fund":false,"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":[0.002306032,0.005570538,0.003576414,0.004137833,0.002084036,0.002533654,0.004771926,0.001910353,0.1070572],"category_scores_gemma":[0.003302507,0.004150075,0.002898458,0.004288196,0.001037737,0.001690981,0.002454786,0.006268081,0.1768635],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001193133,"about_ca_system_score_gemma":0.001917415,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002476881,"about_ca_topic_score_gemma":0.006319006,"domain_scores_codex":[0.996439,0.000709135,0.0003620788,0.001144861,0.00096435,0.0003807454],"domain_scores_gemma":[0.9989164,0.0002466602,0.00008579293,0.0004640183,0.0001786067,0.0001086396],"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":[0.000811052,0.0002554369,0.0006321252,0.004346914,0.0003839665,0.0002190721,0.0003588611,0.001619103,0.2451445,0.007703542,0.6606342,0.0778912],"study_design_scores_gemma":[0.0002610823,0.0001971074,0.001582233,0.0002294209,0.0002004204,0.0004622843,0.00003867604,0.001788741,0.114884,0.006754903,0.8734087,0.0001925495],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"protocol","genre_scores_codex":[0.004625741,0.004750595,0.281762,0.000608485,0.001215952,0.003198236,0.5804094,0.08534423,0.03808532],"genre_scores_gemma":[0.005677719,0.00154867,0.1919617,0.001019611,0.0002607865,0.006514125,0.7333241,0.02712499,0.03256829],"genre_candidate":"protocol","genre_consensus":null,"teacher_disagreement_score":0.1070572,"threshold_uncertainty_score":0.3581421,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0177872062274932,"score_gpt":0.2040609414632281,"score_spread":0.186273735235735,"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."}}