{"id":"W3122362663","doi":"","title":"The management of natural resources under asymmetry of information","year":2015,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Economic theories and models","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Center for Interuniversity Research and Analysis on Organizations; Université du Québec à Montréal; Université de Montréal","funders":"","keywords":"Non-renewable resource; Information asymmetry; Moral hazard; Incentive; Adverse selection; Renewable resource; Natural resource; Private information retrieval; Resource (disambiguation); Principal (computer security); Resource management (computing); Natural resource economics; Economics; Business; Environmental economics; Microeconomics; Risk analysis (engineering); Computer science; Renewable energy; Ecology; Computer security","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":[0.004685748,0.0005344287,0.001103374,0.001067743,0.0007285106,0.003565664,0.001633747,0.003130523,0.003085189],"category_scores_gemma":[0.01016259,0.0004734405,0.0007939236,0.001285017,0.003849497,0.005626286,0.002524858,0.001998624,0.0003354325],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002455233,"about_ca_system_score_gemma":0.002071017,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001239041,"about_ca_topic_score_gemma":0.001010117,"domain_scores_codex":[0.9966155,0.00144652,0.000236229,0.0003634348,0.0010224,0.0003159658],"domain_scores_gemma":[0.9937178,0.003985867,0.001092078,0.0005012401,0.0005043175,0.0001986805],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00002152042,0.00002862146,0.0004629165,0.0003148311,0.00005177934,0.0001702434,0.0001316888,0.05987535,0.0009126689,0.9036053,0.002098287,0.0323268],"study_design_scores_gemma":[0.00001052749,0.00002269309,0.000386586,0.0001123066,0.00001178921,0.00007898663,0.00005537671,0.03498617,0.0003499495,0.9559957,0.007966234,0.00002375269],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04269611,0.03511702,0.8079915,0.01945958,0.0008770036,0.0001894577,0.0003164301,0.0001534526,0.09319954],"genre_scores_gemma":[0.8819451,0.03891456,0.06466456,0.001511643,0.001552036,0.0003038947,0.000115523,0.00006918517,0.01092356],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004685748,"threshold_uncertainty_score":0.02478087,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03488473540124276,"score_gpt":0.2779453797898475,"score_spread":0.2430606443886048,"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."}}