{"id":"W6888930675","doi":"10.25345/c5x34mt2m","title":"MassIVE MSV000088942 - Qtof_DDA_POS_MZML_WS_metabolomics_annotation","year":2022,"lang":"en","type":"dataset","venue":"UC San Diego","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Identification (biology); Process (computing); Work (physics); Set (abstract data type)","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":[],"consensus_categories":[],"category_scores_codex":[0.001186095,0.0044524,0.002562709,0.004927231,0.001836346,0.003301856,0.004388114,0.00354404,0.1042619],"category_scores_gemma":[0.004284673,0.00125281,0.002502326,0.006339658,0.0006673568,0.001451497,0.00288929,0.002029143,0.1190258],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00164719,"about_ca_system_score_gemma":0.00351003,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02279062,"about_ca_topic_score_gemma":0.04006053,"domain_scores_codex":[0.9987913,0.0001443254,0.0001065815,0.00041937,0.0003079363,0.0002305312],"domain_scores_gemma":[0.9984013,0.0004858492,0.000148301,0.0003979928,0.0003403629,0.0002261007],"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":[0.000285786,0.00003520564,0.001007766,0.001234386,0.0001077407,0.00006841677,0.00004884669,0.0005984426,0.002041343,0.000919893,0.9903261,0.003326072],"study_design_scores_gemma":[0.000611983,0.00004622475,0.004645617,0.0003465632,0.0001903594,0.0001579314,0.00008972541,0.001649083,0.003203016,0.003628939,0.9853272,0.0001032611],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002465686,0.000116521,0.0002244018,0.00006575097,0.00003890133,0.00001308333,0.9967054,0.001490844,0.001098541],"genre_scores_gemma":[0.0005124588,0.00006637898,0.000747874,0.00006526137,0.000006844699,0.00005184891,0.997721,0.000264746,0.0005634596],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1042619,"threshold_uncertainty_score":0.3487906,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01782634550054732,"score_gpt":0.273455162611969,"score_spread":0.2556288171114217,"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."}}