{"id":"W7084447385","doi":"","title":"Rapid Scaling of Compositional Uncertainty from Sample to Population Levels","year":2025,"lang":"en","type":"article","venue":"ArXiv.org","topic":"Library Science and Administration","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Population; Estimator; Sample (material); Sampling (signal processing); Variance (accounting); Identification (biology); Scaling; Escapement","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02080465,0.0008849508,0.001291992,0.002602969,0.00125316,0.002868094,0.002184746,0.00162752,0.001742265],"category_scores_gemma":[0.1088745,0.001424462,0.001633598,0.001824593,0.002772086,0.005755273,0.006449067,0.003301657,0.0003941991],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001585243,"about_ca_system_score_gemma":0.001187705,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005277858,"about_ca_topic_score_gemma":0.004958084,"domain_scores_codex":[0.9931461,0.003500651,0.0003611951,0.001652172,0.001155647,0.0001842883],"domain_scores_gemma":[0.9290997,0.05241882,0.004910928,0.009513984,0.003460811,0.0005956552],"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":[0.0003228577,0.0001554887,0.08600907,0.0008503032,0.001028279,0.000610934,0.00276289,0.3714707,0.01771566,0.1479646,0.004049255,0.3670599],"study_design_scores_gemma":[0.00004412939,0.00008730632,0.01509153,0.0001595488,0.000132652,0.0002915928,0.0003068541,0.7491531,0.005393508,0.2251959,0.004045641,0.0000981909],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06347676,0.0008215571,0.9315702,0.0009112377,0.00009548956,0.0001060292,0.0002546862,0.0007604584,0.002003589],"genre_scores_gemma":[0.6108115,0.0009538937,0.3843634,0.0006756637,0.0002849228,0.0003789189,0.0008706456,0.0003946484,0.001266372],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02080465,"threshold_uncertainty_score":0.1100268,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08580608862995029,"score_gpt":0.3472112250590623,"score_spread":0.261405136429112,"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."}}