{"id":"W2163792624","doi":"10.1139/x09-019","title":"Systematic sampling of discrete and continuous populations: sample selection and the choice of estimator","year":2009,"lang":"en","type":"article","venue":"Canadian Journal of Forest Research","topic":"Census and Population Estimation","field":"Mathematics","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Estimator; Statistics; Selection (genetic algorithm); Sampling (signal processing); Sample size determination; Mathematics; Sampling design; Best linear unbiased prediction; Population; Inference; Population size; Sample (material); Econometrics; Computer science; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.09564446,0.000717448,0.002423474,0.002152858,0.00117968,0.002132458,0.002214832,0.002205745,0.00161581],"category_scores_gemma":[0.2655872,0.0009278645,0.00109649,0.002446763,0.005517792,0.003993169,0.002796412,0.002330438,0.0003909335],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001401351,"about_ca_system_score_gemma":0.002652917,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001927259,"about_ca_topic_score_gemma":0.002385515,"domain_scores_codex":[0.8882366,0.0970266,0.003064002,0.003775772,0.007286328,0.0006106463],"domain_scores_gemma":[0.8353329,0.1420822,0.004215944,0.0130827,0.004629276,0.0006570846],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003190829,0.0001467311,0.02683613,0.001150192,0.0006899661,0.0002941131,0.00166985,0.0144543,0.001767438,0.7177436,0.004378942,0.2305496],"study_design_scores_gemma":[0.0003202789,0.0004397361,0.01128948,0.001084414,0.0002303744,0.0004949465,0.0006360231,0.06875961,0.002527082,0.8982617,0.01582563,0.0001307029],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0109677,0.0009086662,0.9846779,0.001167548,0.0001039992,0.0003255679,0.00009703857,0.00007470629,0.001676792],"genre_scores_gemma":[0.1988413,0.001079022,0.7955825,0.0008839981,0.0002136814,0.002065973,0.0002648728,0.00007858922,0.0009901399],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.09564446,"threshold_uncertainty_score":0.5058223,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1436628744441173,"score_gpt":0.4164620124043868,"score_spread":0.2727991379602694,"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."}}