{"id":"W4406782797","doi":"10.3390/wind5010002","title":"A Wind Offset Paradox: Alberta’s Wind Fleet Displacing Greenhouse Gas Emissions and Depressing Future Offset Values","year":2025,"lang":"en","type":"article","venue":"Wind","topic":"Climate Change Policy and Economics","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Canada First Research Excellence Fund; University of Alberta","keywords":"Offset (computer science); Greenhouse gas; Environmental science; Meteorology; Carbon offset; Atmospheric sciences; Geography; Physics; Geology; Oceanography; Computer science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0005047122,0.0002095795,0.0002914859,0.000640947,0.001199012,0.002575102,0.0006965867,0.000690632,0.00323865],"category_scores_gemma":[0.001275609,0.0001372261,0.000314659,0.001051993,0.001196243,0.001358738,0.0005351806,0.0008927972,0.0001331704],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009491782,"about_ca_system_score_gemma":0.00760664,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8062948,"about_ca_topic_score_gemma":0.8982958,"domain_scores_codex":[0.9998042,0.0000232191,0.000004401001,0.00002643004,0.00008524305,0.0000565774],"domain_scores_gemma":[0.9996473,0.00006663767,0.00005380122,0.00002355904,0.0001424027,0.000066378],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0009631682,0.0002436621,0.2525214,0.0003822806,0.0002774465,0.004966202,0.001862222,0.2857317,0.008450847,0.30374,0.05685896,0.08400206],"study_design_scores_gemma":[0.0001670368,0.0001870667,0.3977124,0.0003047926,0.0002270174,0.0009621382,0.01124173,0.2912929,0.004315834,0.1558655,0.1374319,0.0002916795],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9065496,0.002296707,0.005001085,0.008945914,0.0001774066,0.00001826201,0.002120388,0.0001450243,0.0747456],"genre_scores_gemma":[0.9947285,0.0004047172,0.0007401124,0.0002481414,0.00001686401,0.000001789319,0.0003380915,0.00001877851,0.00350294],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1937052,"threshold_uncertainty_score":0.3896919,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03533748739373063,"score_gpt":0.2588293947605442,"score_spread":0.2234919073668136,"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."}}