{"id":"W6908533835","doi":"10.3389/fgene.2020.612515.s001","title":"Image_1_A Distributed Whole Genome Sequencing Benchmark Study.TIF","year":2020,"lang":"en","type":"other","venue":"Figshare","topic":"Physics and Engineering Research Articles","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Concordance; Benchmark (surveying); DNA sequencing; Genomics; Whole genome sequencing; Pipeline (software); Genome; Deep sequencing","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.003123479,0.002155361,0.001579211,0.00352274,0.001378353,0.002630512,0.004072822,0.00213955,0.2093076],"category_scores_gemma":[0.006636515,0.001099419,0.00191297,0.003968834,0.0004946188,0.001809401,0.001936768,0.001886607,0.07319803],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00130291,"about_ca_system_score_gemma":0.00135233,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01394692,"about_ca_topic_score_gemma":0.0188033,"domain_scores_codex":[0.9985221,0.0001883752,0.00009251637,0.000407301,0.0005784137,0.0002113256],"domain_scores_gemma":[0.9968647,0.001453661,0.0001446705,0.0006162869,0.0006909223,0.0002297511],"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":[0.0005867284,0.0001384696,0.002289713,0.001153566,0.0001642726,0.0001963711,0.00009771797,0.002294575,0.008582572,0.002050485,0.9605395,0.02190605],"study_design_scores_gemma":[0.001151789,0.0003274786,0.02348387,0.0004092744,0.0001703939,0.0008645596,0.0001991434,0.0257935,0.02472323,0.008830179,0.9138169,0.0002297221],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.006069255,0.0002978016,0.01412043,0.0007924372,0.0006268614,0.000310646,0.9133477,0.04574421,0.01869062],"genre_scores_gemma":[0.0105894,0.0001981778,0.02622197,0.0004541329,0.0001068291,0.0006686217,0.9384757,0.01620948,0.007075748],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.7906923,"threshold_uncertainty_score":0.7002038,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02446720975105685,"score_gpt":0.2267546483942099,"score_spread":0.2022874386431531,"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."}}