{"id":"W6977414597","doi":"10.6084/m9.figshare.26777263.v1","title":"Additional file 1 of Fairy: fast approximate coverage for multi-sample metagenomic binning","year":2024,"lang":"en","type":"article","venue":"Figshare","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Metagenomics; Key (lock); Window (computing); Identification (biology); File format","routes":{"ca_aff":true,"ca_fund":false,"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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.003410846,0.002312668,0.002159519,0.004294328,0.001909203,0.003356752,0.004017751,0.001768748,0.80644],"category_scores_gemma":[0.03151848,0.001478301,0.00204755,0.006814173,0.0006927658,0.003409628,0.002437338,0.002072657,0.3082963],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00141656,"about_ca_system_score_gemma":0.00260273,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00667125,"about_ca_topic_score_gemma":0.01171159,"domain_scores_codex":[0.9983608,0.0002817393,0.0001406457,0.0005950592,0.0003814958,0.0002402295],"domain_scores_gemma":[0.9835343,0.01194076,0.0006064997,0.001831337,0.001496693,0.0005905072],"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":[0.00034139,0.00006860435,0.002332245,0.002160896,0.0001287581,0.00006184997,0.00009348165,0.001423248,0.001099223,0.001304373,0.9823365,0.008649516],"study_design_scores_gemma":[0.002311858,0.0002093113,0.01792906,0.001290225,0.0004245243,0.0005599143,0.0003451704,0.01090861,0.006657399,0.02390676,0.9351186,0.0003387461],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"software","genre_scores_codex":[0.0002325499,0.00003095746,0.002674633,0.00005199341,0.00005509812,0.00005719472,0.9914685,0.004388974,0.00104004],"genre_scores_gemma":[0.007307894,0.00009824453,0.01873369,0.0003555809,0.0000905805,0.0008603215,0.9531347,0.01432406,0.005094904],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.80644,"threshold_uncertainty_score":0.2760898,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04160755707201078,"score_gpt":0.2641637513621672,"score_spread":0.2225561942901564,"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."}}