{"id":"W4255180537","doi":"10.22215/etd/2016-11234","title":"Statistical Properties of the Signal-to-Noise Crossover Dose Based on the Hill Model as a Point of Departure for Health Risk Assessment","year":2016,"lang":"en","type":"dissertation","venue":"","topic":"Air Quality and Health Impacts","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"McGill University; University of Ottawa","keywords":"Statistics; Extrapolation; Benchmark (surveying); Point estimation; Mathematics; Noise (video); Crossover; Estimation; Econometrics; Algorithm; Computer science; Machine learning; Artificial intelligence; Engineering; Geography","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":[],"consensus_categories":[],"category_scores_codex":[0.01731679,0.0009097088,0.001555436,0.001667717,0.0004070689,0.00156971,0.00183182,0.001244139,0.002027412],"category_scores_gemma":[0.03881522,0.0004298872,0.002406683,0.001300165,0.002034872,0.00174172,0.001116399,0.002852202,0.000448755],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001768308,"about_ca_system_score_gemma":0.001239985,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003343811,"about_ca_topic_score_gemma":0.002287674,"domain_scores_codex":[0.9932614,0.002970207,0.0002863852,0.001441619,0.001794833,0.0002456088],"domain_scores_gemma":[0.9537694,0.03764917,0.002850162,0.003659375,0.001797392,0.000274495],"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":[0.001285847,0.0005834895,0.06223275,0.00133368,0.001740949,0.0006261677,0.001192124,0.5302468,0.03384651,0.1559385,0.00527607,0.2056971],"study_design_scores_gemma":[0.00004888215,0.0009069225,0.0293442,0.0001100754,0.0005611182,0.0003913036,0.0001379431,0.8937929,0.01033387,0.05969441,0.00451265,0.0001656511],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1029139,0.002298,0.8869995,0.0005379525,0.0001157258,0.0003553002,0.0008658461,0.0004605865,0.00545309],"genre_scores_gemma":[0.8366686,0.003150751,0.1501753,0.00049946,0.000198633,0.0007845225,0.001909989,0.0002534278,0.006359316],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01731679,"threshold_uncertainty_score":0.09158105,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04076098618686947,"score_gpt":0.3576702910772224,"score_spread":0.3169093048903529,"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."}}