{"id":"W2047652593","doi":"10.1080/15298660108984622","title":"Exposure Estimation in the Presence of Nondetectable Values: Another Look","year":2001,"lang":"en","type":"article","venue":"AIHAJ - American Industrial Hygiene Association","topic":"Occupational Health and Safety Research","field":"Health Professions","cited_by":139,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Statistics; Limit (mathematics); Standard deviation; Set (abstract data type); Mean squared error; Software; Absolute deviation; Statistical software; Root mean square; Estimation; Maximum likelihood; Square root; Variety (cybernetics); Selection (genetic algorithm); Computer science; Mathematics; Data mining; Artificial intelligence; Engineering","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":[],"consensus_categories":[],"category_scores_codex":[0.003943844,0.0001319234,0.0003300946,0.0002041844,0.000402089,0.00001273497,0.0003074897,0.0002560731,0.0002861404],"category_scores_gemma":[0.004970073,0.0001047178,0.0000604367,0.001628972,0.00008996716,0.0002592004,0.00004978254,0.0008685413,0.0001185258],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007659855,"about_ca_system_score_gemma":0.0008694225,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008323042,"about_ca_topic_score_gemma":0.0007129358,"domain_scores_codex":[0.9953703,0.002019768,0.0007776697,0.0002479189,0.0009462886,0.0006380958],"domain_scores_gemma":[0.9940028,0.00437079,0.0008892876,0.0003243782,0.0003430876,0.00006966812],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004134078,0.0001358572,0.9277634,0.00002380907,0.00001805966,0.000001889532,0.002545038,0.0005136529,0.00009030019,0.0002242127,0.006369813,0.06190055],"study_design_scores_gemma":[0.003405652,0.0009567806,0.9648207,0.0002150459,0.00002996873,0.000001183346,0.008096901,0.004292306,0.00009718415,0.0009048139,0.01692916,0.000250294],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9757315,0.00004722133,0.0005355605,0.006556743,0.0005062324,0.001902568,0.00004887286,0.00004283032,0.01462848],"genre_scores_gemma":[0.9964795,0.00008056989,0.0002295735,0.0005909408,0.0004389194,0.0003022744,0.00004705,0.00001707996,0.001814079],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06165026,"threshold_uncertainty_score":0.9982806,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0804929666418748,"score_gpt":0.4189615991771426,"score_spread":0.3384686325352678,"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."}}