{"id":"W584124344","doi":"10.22004/ag.econ.314678","title":"Macroeconomic Impact and Benefit/Cost Analysis of Transportation and Mining Developments in the Northwest Territories","year":2021,"lang":"en","type":"article","venue":"AgEcon Search (University of Minnesota, USA)","topic":"Coal and Coke Industries Research","field":"Energy","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"U.S. Department of Transportation; U.S. Department of Energy","keywords":"Economic impact analysis; Cost–benefit analysis; Transport economics; Transport engineering; Business; Regional science; Environmental planning; Natural resource economics; Economics; Geography; Engineering; Civil engineering; Political science","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":[0.0002324043,0.00008307293,0.0002443028,0.0002987526,0.000109943,0.00002203399,0.0001611116,0.00006253049,0.0003761572],"category_scores_gemma":[0.00001072359,0.00008236327,0.00006594018,0.000699392,0.0001723279,0.0002131677,0.0000507228,0.0001148451,0.000001433315],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004406623,"about_ca_system_score_gemma":0.00009037088,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.04802852,"about_ca_topic_score_gemma":0.4266495,"domain_scores_codex":[0.9992324,0.0000580414,0.0001400742,0.0001998062,0.0001798373,0.0001898935],"domain_scores_gemma":[0.9994512,0.0001864537,0.00005359731,0.0001395291,0.0001036974,0.00006554485],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007776133,0.00004369778,0.928739,0.00002898053,0.0003418275,0.00009164347,0.00964499,0.000394431,0.0003359477,0.0003122169,0.00002023074,0.05996926],"study_design_scores_gemma":[0.0004305139,0.00004441311,0.9786975,0.00001541037,0.00008121404,0.000002957394,0.01801407,0.0003959051,0.0003397278,0.0000186768,0.001883972,0.0000756464],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9988242,0.00009554231,0.000005830085,0.0002932104,0.00001264769,0.00007037504,0.0002121697,0.00000255133,0.0004834505],"genre_scores_gemma":[0.9988427,0.0003798086,0.000109573,0.000008773362,0.000006784026,4.944462e-7,0.0002205268,0.000003676362,0.0004276697],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.378621,"threshold_uncertainty_score":0.9583107,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0280137355485488,"score_gpt":0.258605974671474,"score_spread":0.2305922391229252,"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."}}