{"id":"W2110424412","doi":"10.1111/j.1467-2979.2007.00270.x","title":"Real options for precautionary fisheries management","year":2008,"lang":"en","type":"article","venue":"Fish and Fisheries","topic":"Capital Investment and Risk Analysis","field":"Economics, Econometrics and Finance","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"College of Engineering, Michigan State University; Michigan State University; Great Lakes Fishery Commission","keywords":"Precautionary principle; Risk analysis (engineering); Risk management; Rubric; Fisheries management; Business; Investment (military); Risk aversion (psychology); Economics; Actuarial science; Expected utility hypothesis; Fishery; Fishing; Finance; Financial economics","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":[0.00007917605,0.0001175231,0.000228672,0.0001011016,0.0003652646,0.00006035033,0.0000825602,0.00006308644,0.0003256278],"category_scores_gemma":[0.00001191078,0.000127902,0.0001146706,0.0001205594,0.0001759669,0.0003119542,0.00004760146,0.00004467805,0.0000324574],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002375755,"about_ca_system_score_gemma":0.00000520014,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000122317,"about_ca_topic_score_gemma":0.00007031819,"domain_scores_codex":[0.9992272,0.000004358576,0.000280197,0.0002720584,0.00002559298,0.0001905422],"domain_scores_gemma":[0.9996481,0.00002291496,0.00008931349,0.0001579253,0.00001846325,0.00006329983],"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":[0.00003925041,0.00008412035,0.08460174,0.00006358371,0.000181835,0.000008065664,0.00101774,0.000004181154,0.00000204117,0.7164584,0.1971636,0.0003755001],"study_design_scores_gemma":[0.0005536501,0.000121765,0.2689659,0.000007561378,0.00003014585,0.00001163371,0.0003909562,0.0007407069,0.00001768978,0.1066724,0.6221584,0.0003291529],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8052744,0.01061657,0.0007767746,0.01111088,0.0007595154,0.0008349588,0.001319105,0.0002371727,0.1690706],"genre_scores_gemma":[0.6100144,0.1960026,0.01973313,0.002568859,0.000670109,0.0008531195,0.001113425,0.00009161259,0.1689528],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.609786,"threshold_uncertainty_score":0.5215693,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04032057475789731,"score_gpt":0.2046000918646056,"score_spread":0.1642795171067083,"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."}}