{"id":"W6958172313","doi":"10.6068/dp14ba89277d032","title":"Trend 2000 - 2002. Statistics Canada. CANSIM: Business Performance and Ownership - Business Cycles | Country: Canada | Table: Financial and taxation statistics for enterprises, by North American Industry Classification System (NAICS) | Variable: Plus: conceptual adjustments, Other services (except public administration) (x 1,000,000) | Units: , 2000-2002. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-018.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"Cell Image Analysis Techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Economic statistics; Business statistics; Census; Official statistics; Summary statistics; Business cycle; Publication; Year-ending","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000291562,0.0006700229,0.0007447822,0.00009357555,0.0001934343,0.0003424225,0.0009951573,0.000532842,0.0003596054],"category_scores_gemma":[0.0001319013,0.0006646241,2.937774e-7,0.0004401848,0.0004250482,0.00009768469,0.0002890415,0.0004004011,0.000002548494],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002788036,"about_ca_system_score_gemma":0.01266257,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9893134,"about_ca_topic_score_gemma":0.9936083,"domain_scores_codex":[0.9965871,0.0002281587,0.0008052124,0.00116953,0.0006201442,0.0005898746],"domain_scores_gemma":[0.9961497,0.0001373935,0.001471275,0.001485487,0.0003879781,0.0003681867],"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":[0.0001326349,0.00006460906,0.0003499057,0.0009516818,0.0002160349,0.00001910658,0.000003001892,0.000008818476,0.00002022468,0.00006750785,0.9976038,0.0005626815],"study_design_scores_gemma":[0.0006507473,0.0001132211,0.0001403799,0.00004958793,0.0004422434,0.00004776734,0.0004124889,0.002979047,8.374503e-7,2.630449e-8,0.9944288,0.0007348977],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00002661708,0.001642541,0.0005407517,0.000004052534,0.0001366959,0.0007241511,0.9963701,0.00004518261,0.0005099483],"genre_scores_gemma":[0.0006904016,0.001464895,0.0005410127,0.0002951277,0.0003106377,0.00008083101,0.9940886,0.0001700172,0.002358405],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01238376,"threshold_uncertainty_score":0.9995805,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01782705541495085,"score_gpt":0.238202841812005,"score_spread":0.2203757863970542,"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."}}