{"id":"W6945269933","doi":"10.25345/c54q7qv4g","title":"MassIVE MSV000090917 - Bottom-up Proteomics Analysis for Adduction of the Broad Spectrum Herbicide Atrazine to Histone","year":2022,"lang":"en","type":"dataset","venue":"UC San Diego","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Environment and Climate Change Canada","funders":"","keywords":"Histone; Atrazine; Broad spectrum; Proteomics; Proteome","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":[],"category_scores_codex":[0.0008696886,0.0008928069,0.00165487,0.001561287,0.0004919491,0.00007352553,0.001995635,0.0004025916,0.03094628],"category_scores_gemma":[0.0006628434,0.0007896891,0.001504231,0.004069136,0.0002719448,0.0001448457,0.0007984291,0.001146614,0.0004703048],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002208586,"about_ca_system_score_gemma":0.0004603215,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003385599,"about_ca_topic_score_gemma":0.01684311,"domain_scores_codex":[0.9946982,0.0004173313,0.001239435,0.001410254,0.001323019,0.0009117915],"domain_scores_gemma":[0.9942671,0.0001730335,0.001799111,0.003271918,0.0002388002,0.000250033],"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":[0.0008219078,0.0002736146,0.0001089002,0.0002680887,0.002602872,0.00001205816,0.0001101392,0.002531386,0.003507806,0.00003121031,0.9896598,0.00007218445],"study_design_scores_gemma":[0.0009055674,0.000424308,0.00124431,0.00007597568,0.006792448,0.00001454717,0.0001616883,0.00008686028,0.005259166,0.0002267762,0.9839184,0.0008899254],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.004225713,0.0003929108,0.0001900848,0.0004703783,0.001617712,0.004532387,0.9883978,0.0001144393,0.00005857475],"genre_scores_gemma":[0.0008704587,0.00003047408,0.001123619,0.0002153011,0.0006272956,0.001566731,0.9924853,0.0002619419,0.002818849],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.03047598,"threshold_uncertainty_score":0.9994554,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0164091872352448,"score_gpt":0.2884817276370745,"score_spread":0.2720725404018297,"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."}}