{"id":"W2110060477","doi":"10.1119/1.19457","title":"Curve fits in the presence of random and systematic error","year":2000,"lang":"en","type":"article","venue":"American Journal of Physics","topic":"Image Processing and 3D Reconstruction","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Autocovariance; Random error; Systematic error; Residual; Physics; Statistics; Statistical error; Function (biology); Statistical physics; Error analysis; Curve fitting; Applied mathematics; Algorithm; Mathematics; Fourier transform; Quantum mechanics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004126927,0.00004703299,0.0002169935,0.00002866804,0.00002770949,0.0000400893,0.0003041646,0.000005902999,0.000001129415],"category_scores_gemma":[0.00003494298,0.00002790016,0.00003669087,0.0003028181,0.0001479451,0.0003060749,0.00001074097,0.00009831956,8.002381e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004665231,"about_ca_system_score_gemma":0.00004808123,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001279567,"about_ca_topic_score_gemma":4.465909e-7,"domain_scores_codex":[0.9992836,0.0001808047,0.0002409673,0.00005588217,0.0001686051,0.00007011347],"domain_scores_gemma":[0.9992611,0.0001989938,0.0003441486,0.0001120502,0.00006517822,0.0000184876],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006335205,0.0001257448,0.001556678,0.001031364,0.00004375322,0.00002568217,0.01602349,0.001170953,0.0003844897,0.00111688,0.00008029449,0.9783773],"study_design_scores_gemma":[0.01956193,0.008052744,0.03477848,0.04496328,0.0006713821,0.02430455,0.03363498,0.6918787,0.02258096,0.1168768,0.0003105435,0.002385654],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.891598,0.0005524558,0.1069932,0.0003314753,0.00009394097,0.00009134984,4.109825e-7,0.000004606289,0.0003345509],"genre_scores_gemma":[0.9944155,0.00002773202,0.005468307,0.00002923264,0.00003599566,9.40915e-7,2.264313e-8,0.000001717933,0.00002061221],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9759917,"threshold_uncertainty_score":0.1137736,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008660299186847398,"score_gpt":0.2401801226900168,"score_spread":0.2315198235031694,"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."}}