{"id":"W6894283194","doi":"10.5683/sp3/3ayqnz","title":"Replication Data and Code for: Give &amp; Take? Child Benefits &amp; Prices in Northern Canada","year":2024,"lang":"en","type":"dataset","venue":"Borealis","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; Acadia University","funders":"","keywords":"Replicate; Replication (statistics); Data file; Code (set theory); Table (database)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.003122865,0.0020394,0.00183531,0.004936591,0.003306642,0.004148816,0.003923818,0.001593188,0.2342279],"category_scores_gemma":[0.025937,0.001372288,0.002007816,0.01377605,0.0008925969,0.001519867,0.00201879,0.002579268,0.09542929],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01603672,"about_ca_system_score_gemma":0.04059937,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9340327,"about_ca_topic_score_gemma":0.9564037,"domain_scores_codex":[0.9972959,0.0003239517,0.0002457247,0.0006172248,0.000822769,0.0006943756],"domain_scores_gemma":[0.9840875,0.002302889,0.0008226452,0.002794713,0.008814167,0.001178164],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003170885,0.000006982662,0.0008494947,0.0001354554,0.00001661777,0.000006268884,0.00003161195,0.0001406961,0.00001163243,0.0003803371,0.9973596,0.001029584],"study_design_scores_gemma":[0.0003953043,0.00001140682,0.01554485,0.0004638573,0.00007152204,0.00003191942,0.000287916,0.0003601571,0.0002076211,0.001286486,0.9812568,0.00008222258],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00009599948,0.0000275641,0.00007013927,0.00009079614,0.00003190754,0.00003439108,0.9981474,0.0001867302,0.001315126],"genre_scores_gemma":[0.001406777,0.00006784753,0.0005815207,0.0001145311,0.00001781149,0.0004490776,0.9910207,0.0003618076,0.005979912],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2342279,"threshold_uncertainty_score":0.7835702,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04781957875652777,"score_gpt":0.3030425117888036,"score_spread":0.2552229330322759,"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."}}