{"id":"W3113002851","doi":"10.1016/j.enconman.2020.113748","title":"Towards robust investment decisions and policies in integrated energy systems planning: Evaluating trade-offs and risk hedging strategies for remote communities","year":2020,"lang":"en","type":"article","venue":"Energy Conversion and Management","topic":"Integrated Energy Systems Optimization","field":"Engineering","cited_by":46,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Victoria","funders":"Mitacs; Marine Environmental Observation Prediction and Response Network; Polar Knowledge Canada","keywords":"Environmental economics; Energy consumption; Renewable energy; Robustness (evolution); Context (archaeology); Energy planning; Risk analysis (engineering); Computer science; Reliability engineering; Operations research; Engineering; Business; Economics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002411288,0.0002497855,0.0002850304,0.0002596969,0.0001876269,0.000199564,0.0001015766,0.00009676181,0.000003016503],"category_scores_gemma":[0.00001957074,0.000234141,0.00002584461,0.0002131294,0.00006107792,0.0001994422,0.0001031336,0.0001106534,1.535166e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008509914,"about_ca_system_score_gemma":0.00001814752,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005655043,"about_ca_topic_score_gemma":0.0003266341,"domain_scores_codex":[0.9989204,0.0001312691,0.0003418663,0.000217314,0.0001518196,0.0002372684],"domain_scores_gemma":[0.9995301,0.00010875,0.00007557281,0.0001331944,0.00003458397,0.0001177808],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000409497,0.000007276241,0.00009301925,0.0002029486,0.0001357617,0.000006952077,0.004043511,0.9440761,0.00007003258,0.03867877,0.0007950324,0.0118497],"study_design_scores_gemma":[0.0009203634,0.0001059137,0.0001808501,0.0003852702,0.00005531813,0.000004327043,0.04529924,0.9380298,0.0001021607,0.0001843917,0.01450194,0.0002304527],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2627707,0.007333058,0.7183971,0.0005236386,0.000634641,0.0006168328,0.00003844028,0.0005350697,0.009150535],"genre_scores_gemma":[0.9890634,0.005668479,0.004611005,0.0003311551,0.00003809536,0.00004821477,0.00008537453,0.00003933337,0.0001148968],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7262928,"threshold_uncertainty_score":0.9547991,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04282716979668463,"score_gpt":0.2504971018224336,"score_spread":0.2076699320257489,"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."}}