{"id":"W6945276902","doi":"10.25345/c5v698d5v","title":"MassIVE MSV000088958 - Qtof_FS_POS_MZML_CS_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":[0.0007717299,0.0009234584,0.001032394,0.001039404,0.0005024439,0.0002384469,0.001641973,0.0004792563,0.3048779],"category_scores_gemma":[0.000572843,0.001037151,0.000448737,0.0009895924,0.000197911,0.0002362889,0.0008773717,0.001668563,0.01900957],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006344517,"about_ca_system_score_gemma":0.0004078155,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005504591,"about_ca_topic_score_gemma":0.000735002,"domain_scores_codex":[0.9948123,0.0005458262,0.0009051053,0.001326465,0.001465591,0.000944695],"domain_scores_gemma":[0.9959731,0.0002557103,0.001169691,0.002084079,0.0002208852,0.0002966133],"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":[0.0001265344,0.0002471865,0.00001059982,0.00009262341,0.0002816418,0.0002748832,0.00005139054,0.0001102965,0.0002331183,0.0002451132,0.9978828,0.000443829],"study_design_scores_gemma":[0.0007676168,0.0001491525,0.0001647804,0.00003181467,0.0004776157,0.00002417907,0.0001177229,0.00002652266,0.00008478206,0.0005772564,0.9964873,0.00109123],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002528565,0.001454453,0.000003710655,0.00006883386,0.002801052,0.0008451681,0.9928243,0.0002456967,0.001503987],"genre_scores_gemma":[0.00005105554,0.0002583587,0.000143441,0.0005474334,0.0006673113,0.0004085639,0.9966381,0.0003008886,0.000984843],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2858683,"threshold_uncertainty_score":0.9992079,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01874276855911456,"score_gpt":0.27613780372035,"score_spread":0.2573950351612355,"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."}}