{"id":"W7132917888","doi":"","title":"Towards Automated Toxicity Testing Using Novel Technologies to Reduce Spectral Overlap and Address Sensitivity Limitations in Environmental In-Vivo NMR","year":2023,"lang":"","type":"dissertation","venue":"TSpace","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Ontario Ministry of Research and Innovation; Natural Sciences and Engineering Research Council of Canada; Krembil Foundation; Centre National de la Recherche Scientifique; Government of Ontario","keywords":"Daphnia magna; Organism; Toxicity; Nuclear magnetic resonance spectroscopy; Metabolomics; Sensitivity (control systems); Model organism","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00305997,0.001023244,0.001040431,0.001169219,0.0003758497,0.001780512,0.001678469,0.0014758,0.002746605],"category_scores_gemma":[0.00280288,0.0006831884,0.0006828571,0.0008399868,0.0008642495,0.00226376,0.001514189,0.002056899,0.001706002],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008400425,"about_ca_system_score_gemma":0.0009723142,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006116527,"about_ca_topic_score_gemma":0.001066653,"domain_scores_codex":[0.9981886,0.0003328615,0.00008113278,0.0003569252,0.0009278509,0.0001125509],"domain_scores_gemma":[0.997566,0.0008046851,0.0004091051,0.0003453904,0.0007766068,0.00009821974],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001361243,0.0001199366,0.001042775,0.0005499857,0.00003948882,0.0001039804,0.000120921,0.002940297,0.9159039,0.002201725,0.00127316,0.07556763],"study_design_scores_gemma":[0.00003210452,0.0008519889,0.002505275,0.0001372258,0.0001088604,0.0005077067,0.0001536428,0.02682573,0.9306955,0.003497948,0.03457395,0.0001101036],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09612317,0.003813504,0.885834,0.001748284,0.0004217578,0.0005308283,0.0007072509,0.004569341,0.006251866],"genre_scores_gemma":[0.1711537,0.006439375,0.8106202,0.001572902,0.0002229468,0.0008683805,0.00104573,0.0006050851,0.00747164],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00305997,"threshold_uncertainty_score":0.01618284,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06154164028711468,"score_gpt":0.3290926075169444,"score_spread":0.2675509672298297,"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."}}