{"id":"W4404581451","doi":"10.13182/pbnc24-45132","title":"Optimizing SMR Implementation and Waste Generation in Ontario's Future Energy Mix Using a Dynamic MILP Approach","year":2024,"lang":"en","type":"article","venue":"","topic":"Urban Planning and Valuation","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Computer science; Environmental economics; Process engineering; Engineering; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001044311,0.0004777469,0.0004674121,0.0008497693,0.0009624106,0.002207921,0.0007737977,0.0008725829,0.004093256],"category_scores_gemma":[0.001556681,0.0006894121,0.0006393474,0.001103541,0.000483613,0.001093477,0.000506438,0.0006167355,0.0002459386],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01713885,"about_ca_system_score_gemma":0.01148161,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6344341,"about_ca_topic_score_gemma":0.8304679,"domain_scores_codex":[0.9994357,0.0001444971,0.00001196387,0.0000534536,0.0001455971,0.0002087893],"domain_scores_gemma":[0.9996424,0.0001445074,0.0000378914,0.00001623613,0.0001039631,0.00005512341],"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":[0.00008922995,0.0000455153,0.003856116,0.00002836056,0.00002863712,0.00007332754,0.00005011919,0.9817075,0.000840692,0.004207553,0.0007809402,0.008291996],"study_design_scores_gemma":[0.00002087495,0.00004087576,0.005468793,0.00000968844,0.0000266479,0.000009467437,0.0002960056,0.9893404,0.0006457421,0.001951641,0.002174373,0.0000155877],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.871617,0.0002946287,0.04371507,0.001272667,0.0000382487,0.0003071387,0.001980618,0.0002068461,0.08056784],"genre_scores_gemma":[0.9862384,0.00006309949,0.006745315,0.00002778535,0.000003030555,0.00003762242,0.0002047245,0.0000291681,0.006650908],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3655659,"threshold_uncertainty_score":0.7354376,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03387929995555031,"score_gpt":0.2709608435215511,"score_spread":0.2370815435660008,"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."}}