{"id":"W4404387947","doi":"10.1016/j.yrtph.2024.105737","title":"A framework for categorizing sources of uncertainty in in silico toxicology methods: Considerations for chemical toxicity predictions","year":2024,"lang":"en","type":"article","venue":"Regulatory Toxicology and Pharmacology","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"In silico; Chemical toxicity; Biochemical engineering; Toxicology; Toxicity; Computational biology; Computer science; Chemistry; Biology; Engineering","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.04911344,0.003621549,0.002599583,0.02209731,0.00432003,0.01232052,0.005494872,0.005213051,0.002332215],"category_scores_gemma":[0.06229208,0.001235812,0.00564291,0.008038946,0.009363716,0.01206606,0.007134438,0.006466862,0.0006435166],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007926835,"about_ca_system_score_gemma":0.01078637,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01418568,"about_ca_topic_score_gemma":0.01080735,"domain_scores_codex":[0.9666707,0.01766839,0.003779373,0.002442341,0.008236282,0.001202871],"domain_scores_gemma":[0.9377653,0.04074617,0.005615154,0.003813226,0.01095178,0.001108445],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00004767416,0.0001322843,0.002903359,0.0007751409,0.0002252809,0.0004303891,0.001912356,0.09452522,0.001298707,0.8361453,0.002753236,0.05885103],"study_design_scores_gemma":[0.00003194867,0.0001037742,0.001190881,0.001327976,0.0001729967,0.0003531103,0.001233858,0.1273724,0.001543127,0.8465141,0.0199855,0.0001703106],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002912122,0.001399238,0.9879591,0.002598461,0.0001079593,0.0003405483,0.0002537454,0.0001892251,0.004239557],"genre_scores_gemma":[0.08855578,0.001369847,0.9071422,0.0006372315,0.0002250334,0.0009193775,0.0004258606,0.00008034411,0.0006442408],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9508865,"threshold_uncertainty_score":0.2597398,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05545822234227964,"score_gpt":0.4079368870394194,"score_spread":0.3524786646971397,"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."}}