{"id":"W4250523022","doi":"10.24124/2009/bpgub564","title":"Socioeconomic factors affecting non-timber forest product collection in the Komi Republic, Russia.","year":2009,"lang":"en","type":"dissertation","venue":"","topic":"Forest Management and Policy","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Library and Archives Canada","funders":"","keywords":"Socioeconomic status; Forestry; Geography; Product (mathematics); Political science; Demography; Sociology; Mathematics; Population","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":[0.0003364561,0.00009297927,0.0001595102,0.0004783431,0.0006034591,0.0006589103,0.0002525681,0.0002073809,0.002460144],"category_scores_gemma":[0.001061145,0.0001134414,0.000242769,0.0009562306,0.0003412521,0.0002910877,0.0007516841,0.000476934,0.0003473423],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001051053,"about_ca_system_score_gemma":0.0009565167,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07495324,"about_ca_topic_score_gemma":0.1277778,"domain_scores_codex":[0.9997049,0.0000888631,0.00002261114,0.00003222856,0.00003227322,0.0001190009],"domain_scores_gemma":[0.9992482,0.0001171783,0.0003528423,0.00003214209,0.00006462634,0.0001848727],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005673221,0.00007188084,0.9953398,0.00000917853,0.00003011867,0.0001323282,0.0009617798,0.00009809816,0.0001871332,0.000322205,0.0002231262,0.002567688],"study_design_scores_gemma":[7.887211e-7,0.00001102782,0.9988198,0.000003548056,0.000004107817,0.00002207266,0.0008517406,0.00005253835,0.00001741656,0.00002293679,0.0001932449,8.80651e-7],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9983231,0.0000846437,0.00001829808,0.000112115,0.000002265379,0.000003503005,0.0002681726,0.000001001925,0.001186868],"genre_scores_gemma":[0.9993945,0.00008178941,0.0000131321,0.000007957427,0.000001932451,0.000003008656,0.0001784737,8.914136e-7,0.0003183125],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07495324,"threshold_uncertainty_score":0.149034,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00834079854350186,"score_gpt":0.2475652352283831,"score_spread":0.2392244366848812,"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."}}