{"id":"W2805993853","doi":"10.1101/265157","title":"Genome survey of the freshwater mussel <i>Venustaconcha ellipsiformis</i> (Bivalvia: Unionida) using a hybrid <i>de novo</i> assembly approach","year":2018,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Aquatic Invertebrate Ecology and Behavior","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Acadia University; Université de Montréal","funders":"Université de Montréal; Ministère de l'Économie, de la Science et de l'Innovation - Québec; Compute Canada","keywords":"Genome; Biology; Mitochondrial DNA; Sequence assembly; Evolutionary biology; Genome size; Genetics; DNA sequencing; Genomics; Gene; Computational biology","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":[0.0002898609,0.0003980924,0.0002586056,0.0007619094,0.0004674704,0.0005098096,0.0002544658,0.0003919755,0.0005891375],"category_scores_gemma":[0.0003746542,0.0002376339,0.0005007781,0.0005681401,0.0001556377,0.0001796287,0.0005600828,0.0002971689,0.0003260998],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002673997,"about_ca_system_score_gemma":0.0003350581,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003192838,"about_ca_topic_score_gemma":0.004857743,"domain_scores_codex":[0.9997445,0.00001956175,0.0000186198,0.000141439,0.00005387654,0.00002203712],"domain_scores_gemma":[0.9998072,0.00003062922,0.00005223804,0.00001974372,0.00005227472,0.00003789009],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001721158,0.000052813,0.04080698,0.0002592153,0.0001009041,0.0002608293,0.000341356,0.001192022,0.9436368,0.0001228439,0.0003353222,0.01271887],"study_design_scores_gemma":[0.00005949959,0.0008469363,0.7970315,0.000145789,0.0003738842,0.002017117,0.0008240719,0.013628,0.1693708,0.0002309099,0.01538987,0.00008168207],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9883811,0.0003428136,0.006176899,0.00003588723,0.000009877999,0.0000407129,0.004129882,0.0001465131,0.0007363287],"genre_scores_gemma":[0.9530727,0.0003498809,0.01716681,0.00008716741,0.000009522016,0.00009132992,0.0278428,0.00008138413,0.001298369],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003192838,"threshold_uncertainty_score":0.006348491,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02358106280495957,"score_gpt":0.2189132450892494,"score_spread":0.1953321822842898,"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."}}