{"id":"W4402481521","doi":"10.3390/environments11090199","title":"Climate Change Adaptation through Renewable Energy: The Cases of Australia, Canada, and the United Kingdom","year":2024,"lang":"en","type":"article","venue":"Environments","topic":"Water-Energy-Food Nexus Studies","field":"Environmental Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Renewable energy; Climate change; Diversification (marketing strategy); Environmental resource management; Natural resource economics; Greenhouse gas; Business; Adaptation (eye); Climate change mitigation; Psychological resilience; Energy policy; Resilience (materials science); Environmental planning; Environmental economics; Economics; Geography; Engineering; Ecology","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":[0.001222059,0.0002504798,0.0002899847,0.001326463,0.01542618,0.003437883,0.0009677768,0.001249366,0.001762173],"category_scores_gemma":[0.003865944,0.0001741256,0.0003224125,0.003477251,0.004346992,0.001189895,0.003339274,0.001710013,0.00008934635],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.06313312,"about_ca_system_score_gemma":0.06231239,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9921266,"about_ca_topic_score_gemma":0.996172,"domain_scores_codex":[0.9977853,0.0004916477,0.00005589333,0.00009820855,0.0005438811,0.001024928],"domain_scores_gemma":[0.9975622,0.0005211739,0.0001735035,0.00007924373,0.001010907,0.0006529365],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.000192245,0.0002298431,0.1658629,0.0006766878,0.0001395865,0.03014414,0.5676304,0.004038443,0.002416297,0.1405663,0.02102338,0.06707978],"study_design_scores_gemma":[0.00001852136,0.00003613154,0.1208134,0.0004871034,0.00006955576,0.001282584,0.7553723,0.001356096,0.000702615,0.002268809,0.1174969,0.00009590122],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9129272,0.002187467,0.0003274025,0.005921936,0.00005509643,0.00008440763,0.0001564267,0.000009450227,0.0783307],"genre_scores_gemma":[0.9921984,0.001441592,0.0002640933,0.0006890627,0.000004139039,0.00002017339,0.00004141758,0.000006056028,0.005335044],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06313312,"threshold_uncertainty_score":0.458065,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0678489948052852,"score_gpt":0.2464723715901786,"score_spread":0.1786233767848934,"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."}}