{"id":"W4388750665","doi":"10.1016/j.erss.2023.103340","title":"From resistance to resilience: A comprehensive bibliometric analysis of carbon pricing public acceptance","year":2023,"lang":"en","type":"article","venue":"Energy Research & Social Science","topic":"Energy, Environment, Economic Growth","field":"Economics, Econometrics and Finance","cited_by":13,"is_retracted":false,"has_abstract":false,"ca_institutions":"Trinity Western University; Western University; York University","funders":"","keywords":"Thematic analysis; Citation; Bibliometrics; Resilience (materials science); Business; Environmental economics; Political science; Public relations; Knowledge management; Sociology; Computer science; Qualitative research; Economics; Social science; Library science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":["bibliometrics"],"domain":null,"study_design":"observational","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":["bibliometrics"],"domain":null,"study_design":"design_other","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"}],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["bibliometrics"],"consensus_categories":["bibliometrics"],"category_scores_codex":[0.004199721,0.0001979249,0.0007209033,0.07127415,0.0007298355,0.0002855135,0.00197741,0.0001285198,0.0002068911],"category_scores_gemma":[0.001622594,0.0002424522,0.0001864533,0.3319675,0.001284066,0.0005767841,0.0009006104,0.000280925,0.0001319824],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008838209,"about_ca_system_score_gemma":0.0001774765,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004674801,"about_ca_topic_score_gemma":0.0008286145,"domain_scores_codex":[0.9956518,0.0001332322,0.0008430324,0.001377894,0.0006750032,0.001318982],"domain_scores_gemma":[0.9975672,0.0005602677,0.00041349,0.0008070334,0.0002594595,0.0003924998],"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":[0.00006451865,0.000213469,0.2376425,0.00002832573,0.0005252509,0.0000215673,0.004123069,0.004984195,0.01750134,0.7240825,0.003509501,0.007303805],"study_design_scores_gemma":[0.0002276911,0.00004847251,0.9546524,0.00001136763,0.00001349628,8.013173e-8,0.0009211328,0.004497058,0.001720028,0.01403561,0.02352854,0.0003441138],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9466089,0.0007278796,0.0004378835,0.001604717,0.0002196595,0.0001392924,0.0001369372,0.00006367812,0.05006108],"genre_scores_gemma":[0.9962267,0.0005123112,0.0003445308,0.0001188222,0.0001678679,0.0000796009,0.00001853861,0.00002649578,0.002505185],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.71701,"threshold_uncertainty_score":0.9886914,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09182355085197103,"score_gpt":0.3338340351475657,"score_spread":0.2420104842955946,"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."}}