{"id":"W2128314779","doi":"10.1139/cjfr-2015-0266","title":"Design-based regression estimation of net change for forest inventories","year":2015,"lang":"en","type":"article","venue":"Canadian Journal of Forest Research","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Estimator; Estimation; Statistics; Regression; Econometrics; Regression analysis; Monte Carlo method; Mathematics; Matching (statistics); Computer science; Economics","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":[0.01611624,0.001031162,0.001226926,0.001459924,0.0002530497,0.0007420318,0.0009654426,0.001069735,0.002349687],"category_scores_gemma":[0.03898515,0.0007323229,0.001515035,0.001310314,0.000535562,0.001065673,0.0009113963,0.0009320084,0.0007386144],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008603111,"about_ca_system_score_gemma":0.000804148,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001534573,"about_ca_topic_score_gemma":0.002506788,"domain_scores_codex":[0.9829625,0.01411932,0.0002626868,0.001224642,0.001243846,0.0001870126],"domain_scores_gemma":[0.9753345,0.01949493,0.001948544,0.002115701,0.001016181,0.00009018492],"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":[0.0006623656,0.000348736,0.06730646,0.0007770226,0.001514685,0.00006745139,0.0002265519,0.5560526,0.009158166,0.02911653,0.001827651,0.3329417],"study_design_scores_gemma":[0.0001796105,0.001124601,0.03229801,0.00006701308,0.0002443234,0.0001927292,0.00004156086,0.9316437,0.005733447,0.02379906,0.004585126,0.00009095708],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02412173,0.0003310117,0.9742167,0.00002805465,0.00001748651,0.0001412873,0.0001651433,0.0002975805,0.0006809253],"genre_scores_gemma":[0.3547771,0.0003093273,0.6404645,0.00006627944,0.00003697551,0.0009524231,0.001073322,0.0001561509,0.002163911],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01611624,"threshold_uncertainty_score":0.0852319,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1893229501045666,"score_gpt":0.3622286588786623,"score_spread":0.1729057087740957,"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."}}