{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0007409265,0.0009476077,0.00105501,0.001036932,0.0005169003,0.0002380231,0.001639105,0.000490772,0.3263741],"category_scores_gemma":[0.0005791705,0.001050087,0.0004442456,0.00104743,0.0002041035,0.0002436712,0.0008844716,0.001670966,0.0199551],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006261781,"about_ca_system_score_gemma":0.0004088247,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004529739,"about_ca_topic_score_gemma":0.0006210288,"domain_scores_codex":[0.9947464,0.0005566331,0.0009201263,0.00134037,0.00147521,0.0009612168],"domain_scores_gemma":[0.9959969,0.0002573413,0.001153545,0.002086618,0.0002050154,0.0003005931],"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":[0.000118795,0.0002559794,0.00001286147,0.00009236928,0.0002857206,0.0002798817,0.00005164525,0.0001139652,0.000196847,0.0002196655,0.9979123,0.0004599606],"study_design_scores_gemma":[0.0007787126,0.0001415304,0.0001606095,0.00003399355,0.0004737838,0.00002440835,0.0001256159,0.00002577729,0.00007020545,0.0004995317,0.99656,0.001105808],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002269264,0.001366186,0.000003805862,0.00007308771,0.00289287,0.0008647365,0.9929423,0.000254594,0.001375484],"genre_scores_gemma":[0.00004091724,0.0002779294,0.0001531911,0.0005552078,0.0006857872,0.0004236533,0.9964311,0.0003115482,0.001120662],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.306419,"threshold_uncertainty_score":0.9991949,"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."}}