{"id":"W2270079946","doi":"","title":"Valuation of Iran s forest and comparison with India and Canada","year":2003,"lang":"en","type":"dissertation","venue":"INFLIBNET","topic":"Agricultural Economics and Policy","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Valuation (finance); Business; Geography; Forestry; Accounting","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000450287,0.0001164484,0.0001961873,0.000006265345,0.00005889978,0.00002693358,0.00005167738,0.00009654394,0.00003476578],"category_scores_gemma":[0.000008380202,0.00004008131,0.0000124286,0.00005105362,0.00001867505,0.00004151428,0.000006365177,0.00007504705,4.65854e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001547092,"about_ca_system_score_gemma":0.00003126942,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.4181251,"about_ca_topic_score_gemma":0.9687256,"domain_scores_codex":[0.999491,0.00001690379,0.0001704655,0.0001395736,0.00008077744,0.0001012805],"domain_scores_gemma":[0.9996411,0.00005513025,0.0001915181,0.00002004533,0.00003482937,0.00005733203],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001673648,0.00005451186,0.9164379,0.0001890431,0.0001240067,0.000003238646,0.001184678,0.00007940735,0.006535941,0.002767674,0.01071351,0.06174268],"study_design_scores_gemma":[0.00008959084,0.000123933,0.9844376,0.00002903692,0.00002094627,0.000002354641,0.0005927177,0.00001638667,0.0002628475,0.0001198651,0.01416591,0.0001388032],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9964357,0.0002659351,2.429715e-8,0.00008615496,0.00005515128,0.0001391941,0.00006405394,0.000003986982,0.002949824],"genre_scores_gemma":[0.9979315,0.00008201475,0.00001503285,0.00007658447,0.00005136187,0.00000664842,0.0009257278,7.534125e-7,0.0009103661],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5506005,"threshold_uncertainty_score":0.5857497,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02195509416676288,"score_gpt":0.2218314010971697,"score_spread":0.1998763069304068,"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."}}