{"id":"W7020729771","doi":"","title":"Long-term supply mix planning of power systems accounting for greenhouse gas emissions","year":2008,"lang":"en","type":"dissertation","venue":"eScholarship@McGill (McGill)","topic":"Climate Change and Environmental Impact","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Greenhouse gas; Global warming; Climate change; Greenhouse effect; Accounting information system; Carbon accounting; Supply chain; Electricity generation","routes":{"ca_aff":false,"ca_fund":true,"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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004916756,0.0008361468,0.0008953001,0.0002196389,0.001147541,0.00007324221,0.0007777163,0.000749536,0.001569144],"category_scores_gemma":[0.000229945,0.0008408347,0.0004875837,0.0003455337,0.0001434326,0.0009262676,0.0002762022,0.0007614222,0.0003504773],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001004433,"about_ca_system_score_gemma":0.00001432024,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00068325,"about_ca_topic_score_gemma":0.0003958454,"domain_scores_codex":[0.9957535,0.0001119177,0.001065358,0.001072158,0.0009705486,0.001026487],"domain_scores_gemma":[0.9975637,0.0002505333,0.0009392104,0.0007726573,0.00003454325,0.0004393266],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.001249751,0.001812386,0.08657692,0.002358222,0.0006306046,0.0005256481,0.0004772602,0.001971147,0.8622929,0.0003741093,0.0005553036,0.04117576],"study_design_scores_gemma":[0.007711239,0.002567748,0.5999271,0.009779307,0.001668005,0.0008578523,0.005685324,0.0003540787,0.2936304,0.001331818,0.06762065,0.008866517],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9753889,0.0004806588,5.195649e-7,0.000004897318,0.0009370923,0.001179698,0.00211479,0.0001282089,0.0197652],"genre_scores_gemma":[0.9909807,0.000642291,0.0001717482,0.00007512984,0.00004158814,0.0001907442,0.001993219,0.0002735239,0.005631093],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5686625,"threshold_uncertainty_score":0.9994043,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03139351446435867,"score_gpt":0.2696781108171271,"score_spread":0.2382845963527684,"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."}}