{"id":"W4386257048","doi":"10.24908/iqurcp16694","title":"The Library of Pseudoalteromonas","year":2023,"lang":"en","type":"article","venue":"Inquiry Queen s Undergraduate Research Conference Proceedings","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Pseudoalteromonas; Natural product; Bacteria; Computational biology; Biology; Set (abstract data type); Product (mathematics); Natural (archaeology); Computer science; Genetics; 16S ribosomal RNA; Biochemistry","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006123366,0.001315217,0.001000396,0.002543561,0.001034969,0.001734613,0.001247928,0.0009059289,0.01802173],"category_scores_gemma":[0.001576069,0.0005599423,0.001183978,0.004500325,0.000384659,0.001292038,0.001652085,0.0009244498,0.0189806],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006202147,"about_ca_system_score_gemma":0.001132176,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001857443,"about_ca_topic_score_gemma":0.002236241,"domain_scores_codex":[0.999159,0.0001187796,0.0001053956,0.0001984205,0.0003020814,0.000116388],"domain_scores_gemma":[0.9992126,0.0001304701,0.00007506715,0.0002082083,0.0002072872,0.0001663632],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.004227075,0.0008395509,0.006064118,0.003592568,0.0002413491,0.002907149,0.0005526805,0.001750889,0.6377616,0.004913695,0.06857207,0.2685772],"study_design_scores_gemma":[0.0002833114,0.001739807,0.01525736,0.0002515682,0.0002376513,0.003505981,0.000332528,0.002646891,0.2032451,0.001981271,0.7703692,0.0001492515],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.3439418,0.02058646,0.06525497,0.002677817,0.001393947,0.002897806,0.4337537,0.02768979,0.1018037],"genre_scores_gemma":[0.134324,0.009859559,0.07250332,0.001515786,0.0001309916,0.001198658,0.7152382,0.001905995,0.06332354],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01802173,"threshold_uncertainty_score":0.06028873,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07855313013954202,"score_gpt":0.3619690056873175,"score_spread":0.2834158755477755,"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."}}