{"id":"W2995217328","doi":"10.1101/2019.12.19.882662","title":"Rapid method for generating designer algal mitochondrial genomes","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Algal biology and biofuel production","field":"Energy","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Biology; Genome; Phaeodactylum tricornutum; Mitochondrial DNA; Cloning (programming); Computational biology; Genome engineering; Synthetic biology; Genetics; Gene; Genome editing; Algae","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":[0.0009431635,0.0008651434,0.0004797516,0.0008908801,0.0004393548,0.0004964439,0.0007188966,0.0005507704,0.003076908],"category_scores_gemma":[0.0008630501,0.0005243374,0.0005470982,0.0005913923,0.0002814871,0.0004723904,0.0008521597,0.00140889,0.002398964],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004615143,"about_ca_system_score_gemma":0.0004408067,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003732517,"about_ca_topic_score_gemma":0.0009709432,"domain_scores_codex":[0.9990589,0.0001776404,0.0001219668,0.0002330001,0.0003280739,0.00008039353],"domain_scores_gemma":[0.9995223,0.00008367033,0.0001015295,0.0001463339,0.0001000487,0.00004602406],"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":[0.00003603476,0.00003471373,0.0001559016,0.0001359811,0.00001433472,0.00008247211,0.00007696504,0.0003639151,0.9880502,0.000959626,0.0005269336,0.009562884],"study_design_scores_gemma":[0.00001854167,0.0001566322,0.0003517569,0.000015448,0.00003200888,0.000269509,0.00003549042,0.002300566,0.9780251,0.0002244076,0.01854815,0.0000223828],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1468428,0.001614143,0.8362826,0.0004339852,0.000242999,0.001338596,0.003911619,0.004207511,0.005125905],"genre_scores_gemma":[0.4033111,0.002347204,0.5714211,0.0002078073,0.00003625168,0.001384833,0.01141194,0.0007412286,0.009138525],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003076908,"threshold_uncertainty_score":0.0102933,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02347324153393128,"score_gpt":0.2460287738092059,"score_spread":0.2225555322752746,"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."}}