{"id":"W6950633359","doi":"10.5683/sp3/midt8k","title":"Replication Data and Code for: Intergenerational Income Mobility Trends in Canada","year":2023,"lang":"en","type":"dataset","venue":"Borealis","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Replicate; Replication (statistics); Data file; Code (set theory); Social mobility; Economic mobility","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":[0.001862919,0.001767159,0.001491237,0.005194898,0.003521962,0.003881813,0.00403136,0.001113043,0.1400306],"category_scores_gemma":[0.01464408,0.001091562,0.001734539,0.01608161,0.0007054402,0.001219449,0.001941545,0.002223237,0.05797118],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01710806,"about_ca_system_score_gemma":0.04720989,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9705405,"about_ca_topic_score_gemma":0.9795905,"domain_scores_codex":[0.9981276,0.0001660443,0.0001399272,0.000399598,0.0006348803,0.0005319411],"domain_scores_gemma":[0.990004,0.0008343166,0.0003846537,0.001536793,0.006480405,0.0007598724],"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":[0.00003107153,0.000007558054,0.001168619,0.0001038014,0.0000184124,0.000009259421,0.00003832327,0.0001827884,0.00001601534,0.0004020651,0.9964239,0.001598247],"study_design_scores_gemma":[0.0003426853,0.00000956044,0.02486676,0.0003612331,0.00006838846,0.00004514278,0.0003175772,0.0007204153,0.0003077491,0.001103925,0.9717719,0.00008475652],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001606067,0.00002417917,0.00006190239,0.00006225025,0.00002238858,0.0000205143,0.9984632,0.0002267316,0.0009583379],"genre_scores_gemma":[0.001417407,0.00005270768,0.0004681898,0.00004768608,0.000008709969,0.0001801119,0.9941925,0.0002469725,0.003385626],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1400306,"threshold_uncertainty_score":0.4684492,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06707843055432748,"score_gpt":0.3420847627637892,"score_spread":0.2750063322094617,"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."}}