{"id":"W3004375104","doi":"","title":"A Prosperity Index for British Columbia: Technical Background","year":2019,"lang":"en","type":"article","venue":"CSLS Research Reports","topic":"Global trade and economics","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Prosperity; Index (typography); Standard of living; Geography; Economic growth; Development economics; Political science; Economics","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.004923762,0.00009775427,0.0004430035,0.0001029343,0.0002026373,0.0009025739,0.0002700156,0.0002375606,0.001799076],"category_scores_gemma":[0.0006437612,0.0001747702,0.0001752685,0.0002970809,0.0001411544,0.0003245716,0.000175418,0.0003868423,0.0004854238],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00052826,"about_ca_system_score_gemma":0.00015974,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0105833,"about_ca_topic_score_gemma":0.01076053,"domain_scores_codex":[0.99743,0.00001978433,0.0007946103,0.0008415853,0.000159673,0.0007543013],"domain_scores_gemma":[0.9985154,0.00008542122,0.0002159297,0.0007218792,0.0002658144,0.0001955311],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001704295,0.0002152428,0.908893,0.0001136688,0.00004423152,0.000112711,0.00001825458,0.00001426886,0.00003932733,0.006933797,0.08186951,0.001728874],"study_design_scores_gemma":[0.0006449568,0.0001761333,0.3249022,0.0000346835,0.000002505829,0.0003619711,0.00007012726,0.0007930855,0.00001270729,0.1209029,0.5517854,0.0003132712],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.882687,0.0008639153,0.00009082213,0.0001940627,0.0005177898,0.001792058,0.0001069591,0.00004678476,0.1137007],"genre_scores_gemma":[0.9893121,0.0001180403,0.0004155102,0.00007837235,0.0001560607,0.0003919138,0.00003196092,0.00003422723,0.009461824],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5839909,"threshold_uncertainty_score":0.9991134,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1612383860185274,"score_gpt":0.316558360740243,"score_spread":0.1553199747217155,"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."}}