{"id":"W4318831733","doi":"10.21203/rs.3.rs-2359061/v1","title":"How does personalized feedback on carbon emissions impact intended climate action?","year":2023,"lang":"en","type":"preprint","venue":"Research Square","topic":"Environmental Education and Sustainability","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"Social Sciences and Humanities Research Council of Canada; Canada Research Chairs","keywords":"Greenhouse gas; Action (physics); Climate change; Environmental science; Carbon fibers; Natural resource economics; Environmental resource management; Environmental economics; Computer science; Economics; Oceanography; Geology; Physics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.002530104,0.0004757418,0.0003363504,0.0003597178,0.0003584886,0.002375592,0.0004971481,0.001743599,0.02851253],"category_scores_gemma":[0.02863851,0.0002235975,0.0003372646,0.0004518911,0.0004182041,0.002905142,0.0008027488,0.001191971,0.002672018],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007754176,"about_ca_system_score_gemma":0.000734035,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003651708,"about_ca_topic_score_gemma":0.002995135,"domain_scores_codex":[0.9985275,0.0007322237,0.00004627986,0.0002520223,0.0002728319,0.000169035],"domain_scores_gemma":[0.982316,0.01426621,0.0007426298,0.0009624345,0.001216815,0.0004959164],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.005454163,0.00425198,0.0800563,0.001061774,0.000536222,0.0005493612,0.002960131,0.09926462,0.01923714,0.06209117,0.04321875,0.6813184],"study_design_scores_gemma":[0.0007079411,0.001847417,0.1759655,0.0005128569,0.001110261,0.0004135527,0.006636777,0.3887139,0.04178952,0.3088651,0.07314516,0.0002920393],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7944797,0.0009814851,0.05789958,0.01400422,0.00138386,0.0001305811,0.001592888,0.002060316,0.1274673],"genre_scores_gemma":[0.9904758,0.0001784271,0.003431947,0.0004575931,0.0000806973,0.00002064264,0.0001467499,0.0001100966,0.005098031],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02851253,"threshold_uncertainty_score":0.09538394,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08446405908340689,"score_gpt":0.4335176692472418,"score_spread":0.3490536101638349,"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."}}