{"id":"W2759640531","doi":"10.1093/forestscience/54.5.507","title":"Estimating Land Rent from the Market Value of Timberland","year":2008,"lang":"en","type":"article","venue":"Forest Science","topic":"Forest Management and Policy","field":"Environmental Science","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Land value; Value (mathematics); Land Values; Agricultural economics; Market value; Economics; Forestry; Geography; Land use; Mathematics; Statistics; Finance; Ecology; Biology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00119594,0.0003476855,0.0006674678,0.001463184,0.0002714244,0.0008960519,0.0007699548,0.0007004825,0.0031699],"category_scores_gemma":[0.007727472,0.0003587075,0.0006744045,0.00122656,0.000395006,0.001836538,0.0004814438,0.0004087741,0.0005608463],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001449024,"about_ca_system_score_gemma":0.0006179961,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02008093,"about_ca_topic_score_gemma":0.02264084,"domain_scores_codex":[0.9995189,0.0001771523,0.00002358287,0.00007382946,0.0001257926,0.00008070754],"domain_scores_gemma":[0.9972433,0.002039098,0.0002244962,0.0001779878,0.0002126348,0.0001025062],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009533409,0.0002834743,0.5111561,0.0001584425,0.0003406893,0.0003892869,0.0001141118,0.381071,0.003649365,0.0216013,0.001974407,0.07830843],"study_design_scores_gemma":[0.00002734207,0.0001059876,0.1200191,0.00001312086,0.00005404295,0.000230959,0.0001099492,0.868458,0.001558172,0.008419077,0.0009762393,0.0000280304],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9768924,0.0003629854,0.0177698,0.0001374023,0.00001192756,0.000029416,0.0007377563,0.00006234366,0.003996004],"genre_scores_gemma":[0.9943527,0.00006789955,0.004597245,0.000006703311,0.000009446398,0.000007698543,0.00028274,0.00001462244,0.0006607929],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02008093,"threshold_uncertainty_score":0.03992808,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01080947615812602,"score_gpt":0.2279378597700057,"score_spread":0.2171283836118797,"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."}}