{"id":"W4385894309","doi":"10.25080/gerudo-f2bc6f59-00f","title":"aPhyloGeo-Covid: A Web Interface for Reproducible Phylogeographic Analysis of SARS-CoV-2 Variation using Neo4j and Snakemake","year":2023,"lang":"en","type":"article","venue":"Proceedings of the Python in Science Conferences","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada; Université de Sherbrooke","keywords":"Computer science; Phylogeography; Data science; Coronavirus disease 2019 (COVID-19); Context (archaeology); Workflow; Phylogenetic tree; Database; Geography; Biology; Infectious disease (medical specialty)","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001338457,0.0001042383,0.0002330359,0.0004180337,0.0001289206,0.00003790549,0.0004058711,0.00005273067,4.979767e-7],"category_scores_gemma":[0.000600446,0.0000792036,0.00009035278,0.002153055,0.0006052383,0.00000506721,0.0003047804,0.00003727833,5.713213e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007195554,"about_ca_system_score_gemma":0.000145445,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000145115,"about_ca_topic_score_gemma":0.0001220438,"domain_scores_codex":[0.9988402,0.000007902679,0.0002973162,0.0004812354,0.0001646742,0.0002086557],"domain_scores_gemma":[0.9991419,0.00002816011,0.000284894,0.0001634311,0.0003603672,0.00002123275],"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":[0.00001951839,0.00001136265,0.1756586,0.00003596296,0.00006105054,1.06204e-8,0.0005668431,0.0001922497,0.8228493,0.0004078057,0.000008099035,0.0001891994],"study_design_scores_gemma":[0.000204751,0.0001279772,0.2196881,0.00002953046,0.0001406005,9.798767e-7,0.001031455,0.01222311,0.7635096,0.002739611,0.0001796344,0.0001245739],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9989356,0.0002597338,0.0001043781,0.0001801486,0.0001007632,0.0002396883,0.00002801179,0.000003050211,0.0001486567],"genre_scores_gemma":[0.9989445,0.0001776616,0.0008003147,0.00002402293,0.00001890651,0.00002033554,0.00000121921,0.000004263742,0.000008787356],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05933965,"threshold_uncertainty_score":0.3229829,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05797028395049003,"score_gpt":0.3319342107216462,"score_spread":0.2739639267711562,"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."}}