{"id":"W7099535000","doi":"","title":"USE OF RETIREMENT SAVINGS BEFORE RETIREMENT IN CANADA","year":2015,"lang":"en","type":"article","venue":"","topic":"Archaeology and Natural History","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Government (linguistics); Work (physics); Consumption (sociology); Investment (military)","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":[0.001092964,0.0003141656,0.0006643374,0.002841087,0.006271724,0.003054925,0.00266437,0.001199411,0.005908231],"category_scores_gemma":[0.006589647,0.0004977472,0.0008336126,0.006556024,0.001097215,0.0008404723,0.002032919,0.001816505,0.0003462261],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.1032722,"about_ca_system_score_gemma":0.1490408,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9992765,"about_ca_topic_score_gemma":0.9997171,"domain_scores_codex":[0.9981433,0.0001377846,0.0001268132,0.0001629272,0.0004771621,0.0009519685],"domain_scores_gemma":[0.9918106,0.0005151348,0.001140911,0.0001763264,0.00371669,0.002640358],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004663909,0.0001599782,0.9278349,0.0002119927,0.0001564283,0.0003606774,0.01096752,0.0006641872,0.0001599869,0.002824294,0.01257202,0.04362173],"study_design_scores_gemma":[0.00002239904,0.00003693907,0.9696075,0.0002639535,0.00007469885,0.0001074136,0.01559196,0.0007868713,0.0001368773,0.0001454372,0.01317492,0.00005103326],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9762381,0.00400971,0.0001023401,0.004357009,0.00008199998,0.00004215961,0.007172171,0.00002654293,0.007969965],"genre_scores_gemma":[0.9889047,0.00202461,0.0001812434,0.0002728727,0.00001387836,0.00001321494,0.001411647,0.0000126894,0.007165203],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1032722,"threshold_uncertainty_score":0.7492958,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07657704218322786,"score_gpt":0.2899233639252962,"score_spread":0.2133463217420684,"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."}}