{"id":"W6963611290","doi":"10.25345/c54m91c16","title":"MassIVE MSV000088948 - Qtof_DIA_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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0007029793,0.0009342276,0.001048787,0.001050161,0.0004771962,0.0002380553,0.001609504,0.0004783966,0.3275733],"category_scores_gemma":[0.0005974327,0.001043494,0.0004600583,0.001001087,0.0001986569,0.0002431788,0.0008543558,0.001569865,0.02216833],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006232584,"about_ca_system_score_gemma":0.0004249289,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004479408,"about_ca_topic_score_gemma":0.0006354584,"domain_scores_codex":[0.994873,0.0005543026,0.0008964158,0.001320002,0.001394821,0.0009614396],"domain_scores_gemma":[0.9960067,0.0002910526,0.001143865,0.002053569,0.0001960158,0.0003087461],"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":[0.0001013042,0.0002728706,0.00001684524,0.0000924163,0.0002889454,0.0002432482,0.00005343901,0.0001075621,0.0001550424,0.0002653419,0.9979595,0.0004435113],"study_design_scores_gemma":[0.0007848558,0.0001344615,0.0001808246,0.00003344438,0.0004805757,0.00001666687,0.0001298039,0.00002572181,0.00006793298,0.0005127917,0.9965346,0.001098279],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002367313,0.001404744,0.00000322705,0.0000700766,0.003000538,0.0008822624,0.9927316,0.0002464966,0.001424336],"genre_scores_gemma":[0.00004378135,0.0002923893,0.0001366829,0.0005780439,0.0006586589,0.0004789554,0.9966208,0.0003076046,0.0008830465],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.305405,"threshold_uncertainty_score":0.9992015,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01750277359202731,"score_gpt":0.2721100054451815,"score_spread":0.2546072318531543,"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."}}