{"id":"W4399572216","doi":"10.32614/cran.package.statcanr","title":"statcanR: Client for Statistics Canada's Open Economic Data","year":2019,"lang":"en","type":"dataset","venue":"","topic":"demographic modeling and climate adaptation","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Economic statistics; Statistics; Computer science; Data science; Mathematics","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":[0.002014393,0.002178645,0.001522243,0.006813638,0.001479431,0.003231222,0.003937544,0.002169461,0.1452304],"category_scores_gemma":[0.01254503,0.001466298,0.001716229,0.01406615,0.0006319836,0.001204586,0.001711548,0.00245724,0.1103442],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009206021,"about_ca_system_score_gemma":0.01990471,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7199072,"about_ca_topic_score_gemma":0.7759551,"domain_scores_codex":[0.9982238,0.0002004945,0.0001963542,0.0002615913,0.0006421093,0.0004755986],"domain_scores_gemma":[0.9905571,0.001795436,0.0005553551,0.001875472,0.004280312,0.0009363868],"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":[0.0000212861,0.000007058123,0.0004228042,0.0001118595,0.00001116096,0.000006993425,0.00001088355,0.0002744035,0.0000170837,0.0004397971,0.9977372,0.0009394411],"study_design_scores_gemma":[0.000205417,0.000005518392,0.004018341,0.0002188119,0.00002296989,0.00001970587,0.00007124606,0.001035786,0.0002539389,0.00225819,0.9918459,0.00004425667],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"software","genre_scores_codex":[0.00003440944,0.000009307632,0.00005616568,0.00003204194,0.000007947874,0.000007081198,0.9991069,0.0002478467,0.0004981143],"genre_scores_gemma":[0.0004383313,0.00003378933,0.0004305034,0.00005304079,0.000005344428,0.00009599511,0.9972504,0.0002363838,0.001456263],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.2800928,"threshold_uncertainty_score":0.5634847,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4295815908096442,"score_gpt":0.4857102101632895,"score_spread":0.05612861935364533,"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."}}