{"id":"W4405059139","doi":"10.2139/ssrn.4987429","title":"Municipal Cost of Living Sentiment Index","year":2024,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Misinformation and Its Impacts","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Index (typography); Cost of living; Business; Computer science; Economics; World Wide Web; Economic growth","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":[0.0003356628,0.0001719853,0.0003220549,0.004556769,0.000355643,0.001310057,0.0002449123,0.0002339687,0.009104921],"category_scores_gemma":[0.004614301,0.00007712463,0.0001793278,0.01035985,0.0001350374,0.0004074793,0.0005584147,0.0003241372,0.002345969],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001615855,"about_ca_system_score_gemma":0.0006991212,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05262044,"about_ca_topic_score_gemma":0.07426075,"domain_scores_codex":[0.9991859,0.0001051924,0.00009069448,0.00005243241,0.0004623665,0.0001034551],"domain_scores_gemma":[0.9965887,0.0002849737,0.001547766,0.00009594404,0.001259175,0.0002234558],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002840606,0.00007965677,0.852712,0.0002646211,0.000178621,0.0001814902,0.0006999732,0.002160449,0.0007143864,0.00510119,0.1053452,0.03227846],"study_design_scores_gemma":[0.000009132016,0.00004649196,0.9365046,0.00003131615,0.00007262437,0.0001134866,0.001359889,0.003381724,0.000600556,0.0004062008,0.05745717,0.00001682086],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8167865,0.0004653751,0.0005856326,0.001019458,0.00009744935,0.00006583919,0.1044466,0.0002188439,0.07631434],"genre_scores_gemma":[0.9361172,0.0003219758,0.0003996406,0.00004155302,0.0001057138,0.00006162851,0.04895607,0.00003772693,0.01395854],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05262044,"threshold_uncertainty_score":0.1046283,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01658700172073682,"score_gpt":0.322010020198791,"score_spread":0.3054230184780542,"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."}}