{"id":"W4403119711","doi":"10.1088/1748-9326/ad8364","title":"Assessment of the Climate Trace global powerplant CO<sub>2</sub> emissions","year":2024,"lang":"en","type":"article","venue":"Environmental Research Letters","topic":"Integrated Energy Systems Optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"National Oceanic and Atmospheric Administration","keywords":"Environmental science; TRACE (psycholinguistics); Trace gas; Power station; Climatology; Climate change; Meteorology; Atmospheric sciences; Environmental resource management; Geography; Geology; Engineering; Oceanography","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0009724253,0.0004141558,0.0002601723,0.00168665,0.0002910583,0.0009823766,0.0008292494,0.0004103098,0.001672037],"category_scores_gemma":[0.003322344,0.0001663913,0.0003253999,0.002640625,0.0003000663,0.001129303,0.000832449,0.0004946212,0.0002582929],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0020697,"about_ca_system_score_gemma":0.00114737,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06330336,"about_ca_topic_score_gemma":0.0799218,"domain_scores_codex":[0.998793,0.0001467917,0.00003364346,0.0001675885,0.0007634927,0.00009541543],"domain_scores_gemma":[0.997547,0.0004940167,0.0005698046,0.0001695066,0.001101075,0.0001186301],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005482294,0.000253234,0.6432534,0.0003011926,0.0005685253,0.0004854693,0.0002337095,0.2000163,0.01381697,0.003838577,0.01063981,0.1260446],"study_design_scores_gemma":[0.0000335859,0.0003183889,0.805896,0.00007595221,0.0001459052,0.0001848077,0.0008065648,0.1431709,0.0264464,0.002229639,0.02061588,0.00007589269],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9413846,0.0005674828,0.01595893,0.0007293022,0.00004935153,0.00007906895,0.01403037,0.0006354987,0.02656542],"genre_scores_gemma":[0.9928567,0.0001054157,0.002705346,0.00005215895,0.000009825456,0.00001922154,0.003627805,0.00004580057,0.0005776377],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06330336,"threshold_uncertainty_score":0.1258698,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01063596414461082,"score_gpt":0.2841976047412955,"score_spread":0.2735616405966847,"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."}}