{"id":"W4296552799","doi":"10.12688/f1000research.123591.1","title":"Squalomix: shark and ray genome analysis consortium and its data sharing platform","year":2022,"lang":"en","type":"preprint","venue":"F1000Research","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"RIKEN Center for Biosystems Dynamics Research; Institute of Genetics; RIKEN; Japan Society for the Promotion of Science; National Institute of Genetics","keywords":"Genome; Biology; Computational biology; Evolutionary biology; Phylogenomics; Gene; Genetics; Phylogenetics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","open_science"],"consensus_categories":[],"category_scores_codex":[0.001578232,0.0003406725,0.0005307948,0.0004639062,0.000305694,0.0002161521,0.001361965,0.0003609281,0.00007873015],"category_scores_gemma":[0.0002805737,0.0003259057,0.0001429242,0.0004309808,0.000212028,0.00001092707,0.01645817,0.0007871222,0.000002077603],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004490519,"about_ca_system_score_gemma":0.0001321819,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009930065,"about_ca_topic_score_gemma":0.0001068334,"domain_scores_codex":[0.9966249,0.0001198786,0.0004111327,0.001874564,0.0004781002,0.000491398],"domain_scores_gemma":[0.9973261,0.00004916797,0.0001711956,0.00207574,0.0001605307,0.0002172105],"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":[0.0007224043,0.0003030937,0.02694054,0.0008913722,0.009136439,0.000179587,0.000230167,0.0007059283,0.946332,0.000326834,0.003106837,0.01112485],"study_design_scores_gemma":[0.004011658,0.002122789,0.1243285,0.0003347968,0.010095,0.0002170032,0.002233252,0.1509858,0.356594,0.003409924,0.3367429,0.008924372],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9854364,0.009706628,0.0008821746,0.0002879216,0.00005382382,0.0006005663,0.002070257,0.00008531534,0.0008769625],"genre_scores_gemma":[0.9776924,0.008319855,0.002444363,0.00009094724,0.0001997044,0.00004887296,0.009147621,0.00005197938,0.002004237],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.589738,"threshold_uncertainty_score":0.9999193,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0978797773406204,"score_gpt":0.3931281672368265,"score_spread":0.2952483898962061,"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."}}