{"id":"W4398836596","doi":"10.7910/dvn/ticzzh","title":"PROSPERED Dataset: Family Cash Benefits","year":2020,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Financial Literacy, Pension, Retirement Analysis","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Cash; Business; Economics; Finance","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":[0.0009691031,0.001090075,0.0009174962,0.00279063,0.0005196047,0.001501955,0.00180224,0.001268588,0.03672005],"category_scores_gemma":[0.005093711,0.0005085529,0.0006119965,0.005568705,0.0002108927,0.0008036064,0.001140529,0.001386686,0.03490435],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001211635,"about_ca_system_score_gemma":0.001605713,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03929409,"about_ca_topic_score_gemma":0.0508495,"domain_scores_codex":[0.9992342,0.0001415649,0.000120225,0.0001906109,0.0002077916,0.0001057227],"domain_scores_gemma":[0.9980096,0.0003948066,0.0004977823,0.0002701356,0.0006522207,0.0001754431],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.00006183709,0.00002922159,0.003861107,0.0002624904,0.00002768893,0.00002770861,0.00002797236,0.0002933499,0.00004103449,0.0007924978,0.991927,0.002648018],"study_design_scores_gemma":[0.000326542,0.00003551058,0.03090177,0.0003425687,0.00003844933,0.0001290192,0.0001420175,0.0009287248,0.0002489458,0.00140379,0.9654619,0.00004080396],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003515694,0.00004868971,0.00004354706,0.00005597892,0.00000943069,0.000009031884,0.9988406,0.00005690879,0.0005841304],"genre_scores_gemma":[0.0009199034,0.00004845944,0.0001982003,0.00004974264,0.000007482585,0.0000738009,0.9979314,0.00001609681,0.0007550004],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.03929409,"threshold_uncertainty_score":0.1228408,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02457648801173515,"score_gpt":0.2247102847804569,"score_spread":0.2001337967687217,"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."}}