{"id":"W2090725078","doi":"10.1366/0003702042641236","title":"Accuracy and Precision of Manual Baseline Determination","year":2004,"lang":"en","type":"article","venue":"Applied Spectroscopy","topic":"Optical Imaging and Spectroscopy Techniques","field":"Medicine","cited_by":74,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Baseline (sea); Accuracy and precision; Computer science; Noise (video); SIGNAL (programming language); Statistics; Mathematics; Artificial intelligence; Geology","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":[0.0002351655,0.0001397322,0.0002816649,0.0001161326,0.00004409052,0.00001689131,0.00006020339,0.00007544985,0.00004680842],"category_scores_gemma":[0.0001093496,0.0001200414,0.00004211445,0.0001411431,0.0001237882,0.00006670567,0.0000383104,0.0001791887,0.00001262116],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006877395,"about_ca_system_score_gemma":0.00005140795,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001920498,"about_ca_topic_score_gemma":0.000002058661,"domain_scores_codex":[0.9990295,0.00001008154,0.0002651294,0.0002645378,0.0002266191,0.0002041897],"domain_scores_gemma":[0.9994106,0.00009309531,0.00008303206,0.0002612881,0.00005137777,0.0001006068],"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":[0.0002315857,0.0001875048,0.0004269658,0.0000584419,0.000009688264,0.000008271414,0.0001064681,9.077713e-7,0.968157,0.01519811,0.0001142252,0.01550084],"study_design_scores_gemma":[0.001115209,0.0004458911,0.002899267,0.00008205012,0.00005465789,0.00003404402,0.00003915182,0.0001539921,0.9805623,0.01415646,0.0003482309,0.00010875],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8523461,0.0002298511,0.1241547,0.001281335,0.00004192363,0.000647577,0.000006266447,0.0002549142,0.02103725],"genre_scores_gemma":[0.7938707,0.000194518,0.2055589,0.0002012365,0.00007913422,0.00001777117,0.00001224156,0.00001724669,0.00004832487],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08140411,"threshold_uncertainty_score":0.4895144,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00954661599449363,"score_gpt":0.3259915098361473,"score_spread":0.3164448938416536,"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."}}