{"id":"W2113091488","doi":"10.1093/toxsci/kfh282","title":"Biologically Motivated Computational Modeling: Contribution to Risk Assessment","year":2004,"lang":"en","type":"letter","venue":"Toxicological Sciences","topic":"Advanced Chemical Sensor Technologies","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health Canada","funders":"","keywords":"Miller; Computer science; Computational model; Computational biology; Cognitive science; Artificial intelligence; Biology; Psychology; Ecology","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"],"consensus_categories":[],"category_scores_codex":[0.0002032643,0.0004182674,0.0005092184,0.0001506029,0.0002642777,0.0001130056,0.0008925067,0.001263771,0.0001511532],"category_scores_gemma":[0.0007854166,0.0002899691,0.0001224844,0.0007196284,0.0005101677,0.0001041197,0.0001935348,0.001877519,0.00009552347],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006704182,"about_ca_system_score_gemma":0.00002940526,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006384012,"about_ca_topic_score_gemma":0.0000010401,"domain_scores_codex":[0.9973472,0.00006722116,0.0004637055,0.0007160301,0.0005839948,0.0008218322],"domain_scores_gemma":[0.9990713,0.0004056545,0.00009809224,0.0001913328,0.0001251659,0.0001084741],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000002565294,0.00002521541,0.00008531618,0.000009093133,0.00001847278,0.00004136343,0.000002519577,0.9763236,0.003924667,0.0007477821,0.01822603,0.0005933458],"study_design_scores_gemma":[0.0006737041,0.001281923,0.001233204,0.000134168,0.00005683967,0.00002775168,0.00002630977,0.5494136,0.006968004,0.3559446,0.08232524,0.001914588],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.3734851,0.0001820934,0.298562,0.317832,0.0006033588,0.001222734,0.000272344,0.005406912,0.00243341],"genre_scores_gemma":[0.8764291,0.00006741807,0.03654458,0.08626255,0.0004027489,0.0001043683,0.0001481276,0.00002179024,0.00001926733],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5029441,"threshold_uncertainty_score":0.9999552,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03011505761892536,"score_gpt":0.284771018240396,"score_spread":0.2546559606214707,"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."}}