{"id":"W4281256844","doi":"10.1002/imt2.25","title":"iMetaLab Suite: A one‐stop toolset for metaproteomics","year":2022,"lang":"en","type":"article","venue":"iMeta","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada; Ministero dello Sviluppo Economico; Ontario Ministry of Economic Development and Innovation; Government of Canada; Canadian Institutes of Health Research; Genome Canada; Ontario Genomics; Ontario Genomics Institute; University of Ottawa","keywords":"Suite; Metaproteomics; Computer science; Geography; Chemistry","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002112651,0.0001475329,0.0002230086,0.00004463194,0.0003706451,0.00003334174,0.0004383175,0.00005212458,0.001619742],"category_scores_gemma":[0.00004934453,0.0001673331,0.0001758068,0.0001739463,0.00003562545,0.00009995866,0.0002607579,0.0002579987,0.00001649241],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001064345,"about_ca_system_score_gemma":0.00004911446,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001724492,"about_ca_topic_score_gemma":0.000001197793,"domain_scores_codex":[0.9989354,0.00001161694,0.0002581294,0.0003529658,0.0001698376,0.0002720588],"domain_scores_gemma":[0.9990659,0.00007846201,0.0001441184,0.0005992363,0.00004922389,0.00006306833],"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":[0.0000943401,0.0002553485,0.00006372914,0.0000705433,0.0001367814,0.000001869721,0.00008112125,0.0001840196,0.9339345,0.04973056,0.003594018,0.01185323],"study_design_scores_gemma":[0.0003835834,0.00003544701,0.000004689769,0.000002680429,0.00007875545,0.00001146217,0.00005736505,0.0007231971,0.5390921,0.03833239,0.4210389,0.0002394603],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.3553122,0.001838741,0.5929781,0.0040245,0.000242153,0.004213445,0.005532538,0.001791266,0.03406699],"genre_scores_gemma":[0.3334866,0.00004379798,0.6347017,0.0005747768,0.0001770193,0.01024583,0.0006694698,0.0001209179,0.01997978],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4174449,"threshold_uncertainty_score":0.9992929,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02824424873421047,"score_gpt":0.2873602402632292,"score_spread":0.2591159915290187,"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."}}