{"id":"W2992263007","doi":"10.56645/jmde.v10i22.388","title":"Bioeconomic Models and the Formative Evaluation of Fisheries-Related Programs","year":2014,"lang":"en","type":"article","venue":"Journal of MultiDisciplinary Evaluation","topic":"Complex Systems and Decision Making","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fisheries and Oceans Canada; Natural Resources Canada; Government of Canada; Canadian Forest Service","funders":"Fisheries and Oceans Canada; Government of Canada","keywords":"Formative assessment; Bioeconomics; Context (archaeology); Management science; Resource (disambiguation); Environmental resource management; Computer science; Fishery; Engineering; Sociology; Economics; Geography","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0496721,0.002166079,0.001215154,0.003632047,0.000797167,0.006969502,0.003393403,0.002703081,0.004002819],"category_scores_gemma":[0.1624262,0.0007295927,0.001006207,0.003184754,0.005208451,0.00754533,0.002475203,0.002706014,0.00039978],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01056954,"about_ca_system_score_gemma":0.006928808,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005449539,"about_ca_topic_score_gemma":0.005478393,"domain_scores_codex":[0.9406281,0.05031581,0.001235003,0.001157674,0.005556608,0.001106789],"domain_scores_gemma":[0.829019,0.1431482,0.01127047,0.006264091,0.008612583,0.00168571],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003955711,0.0003557359,0.005122431,0.0004851131,0.0002296282,0.0000715068,0.0005544367,0.4145955,0.0003399827,0.5167097,0.002054824,0.05908559],"study_design_scores_gemma":[0.0001572143,0.0005492521,0.002132848,0.000529002,0.0001097485,0.00003195879,0.0005309629,0.2950594,0.001039965,0.6894401,0.01032425,0.00009529591],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.135544,0.008335716,0.7281658,0.0146072,0.0007987404,0.002195059,0.001129926,0.0004465297,0.108777],"genre_scores_gemma":[0.8516885,0.004059597,0.1341105,0.0007334626,0.0002427091,0.002155398,0.0003318221,0.00008853168,0.006589414],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0496721,"threshold_uncertainty_score":0.2626944,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2501084245607457,"score_gpt":0.4341269798821111,"score_spread":0.1840185553213655,"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."}}