{"id":"W2527706370","doi":"","title":"Evaluating the Russian Forest Sector: Market Orientation and Its Characteristics","year":2001,"lang":"en","type":"article","venue":"IIASA PURE (International Institute of Applied Systems Analysis)","topic":"Russia and Soviet political economy","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; International Institute for Applied Systems Analysis; University of Ottawa","keywords":"Market orientation; Linear discriminant analysis; Orientation (vector space); Set (abstract data type); Order (exchange); Identification (biology); Barter; Market analysis; Business; Cash; Rough set; Industrial organization; Computer science; Marketing; Artificial intelligence; Economics; Mathematics; Finance","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001289043,0.0001334956,0.0003216941,0.0001810449,0.000387959,0.0002100396,0.000338786,0.00009909553,0.0003141709],"category_scores_gemma":[0.000140643,0.0001042292,0.0001287519,0.000416853,0.0002051397,0.0002885492,0.00004722214,0.0001132355,0.00001775106],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001159492,"about_ca_system_score_gemma":0.0001321135,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001151756,"about_ca_topic_score_gemma":0.001540887,"domain_scores_codex":[0.9982458,0.00008933442,0.0005513001,0.0002840271,0.0005936887,0.0002358191],"domain_scores_gemma":[0.9990483,0.0001496272,0.0003637867,0.0001828845,0.0001309834,0.0001244406],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003897199,0.00002958624,0.008600405,0.00001595885,0.0005172677,0.000003280803,0.001445937,0.00138567,0.00004078127,0.9872655,0.00009236427,0.0005642213],"study_design_scores_gemma":[0.001816082,0.0001216586,0.2360313,0.0001690274,0.00221848,0.00001913689,0.009229884,0.2838793,0.00002962511,0.01684156,0.4486317,0.001012274],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6574961,0.00007288355,0.001103821,0.001681061,0.001052036,0.0004321602,0.00003970322,0.00003165013,0.3380906],"genre_scores_gemma":[0.9962423,0.0001103288,0.00008570797,0.0001055191,0.0006823611,0.00006163546,0.00005977487,0.000007719712,0.002644671],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.970424,"threshold_uncertainty_score":0.4250343,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04732772398181508,"score_gpt":0.3449216714672342,"score_spread":0.2975939474854192,"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."}}