{"id":"W3130197036","doi":"10.1139/cjfr-2020-0379","title":"Realized and potential efficiency for post-stratified estimation in a national forest inventory","year":2021,"lang":"en","type":"article","venue":"Canadian Journal of Forest Research","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Stratification (seeds); Population stratification; Statistics; Forest inventory; Environmental science; Spatial variability; Spatial ecology; Spatial analysis; Computer science; Mathematics; Forest management; Ecology","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.01111001,0.0004304561,0.0004163393,0.0007209321,0.0004149952,0.001238373,0.0007493437,0.0003149098,0.0008301574],"category_scores_gemma":[0.02581532,0.0003241789,0.000491582,0.00130217,0.0004531233,0.001507377,0.0009711966,0.0004859352,0.0003988873],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001261505,"about_ca_system_score_gemma":0.001745314,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01370195,"about_ca_topic_score_gemma":0.03320473,"domain_scores_codex":[0.9959579,0.002352836,0.0002464302,0.0004138373,0.0007377563,0.0002911272],"domain_scores_gemma":[0.9871257,0.00666252,0.0009181111,0.003016319,0.00213384,0.0001435643],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0009764961,0.000332189,0.3877322,0.0002142952,0.000268588,0.0001785848,0.001396406,0.1404259,0.01322389,0.01708619,0.001555368,0.43661],"study_design_scores_gemma":[0.00008743713,0.0005644491,0.4531549,0.0001453252,0.0002480141,0.0001819199,0.001140824,0.4957761,0.01745912,0.02470794,0.006425747,0.000108409],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.689945,0.0003681923,0.3015364,0.0003438203,0.00003203094,0.0003018523,0.0009787128,0.0003895316,0.006104435],"genre_scores_gemma":[0.8255395,0.00008940419,0.1728534,0.0000381408,0.000009997865,0.0000995014,0.0008148814,0.00002835173,0.0005268583],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.98889,"threshold_uncertainty_score":0.05875605,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03386202835227265,"score_gpt":0.3175082595691643,"score_spread":0.2836462312168917,"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."}}