{"id":"W6901600477","doi":"10.6068/dp14ba8cebceb13","title":"Most Recent Data (2003). Statistics Canada. CANSIM: Seniors - Work and Retirement | Country: Canada | Table: Survey of innovation, selected service industries, innovative business units using sources of information needed for suggesting or contributing to the development of innovation | Variable: Low importance, Contract drilling (except oil and gas), Suppliers of software, hardware, materials or equipment | Units: %, 2003. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-186.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Census; Official statistics; Economic statistics; Work (physics); Population; Socioeconomic status; Descriptive statistics; Service (business); Social security; Social statistics","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":[0.002551916,0.002360363,0.002781767,0.008126969,0.003809956,0.004897124,0.005284586,0.001605937,0.08858884],"category_scores_gemma":[0.02103173,0.001808068,0.002099216,0.04486373,0.0006451166,0.002159071,0.00238717,0.003026773,0.05494006],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05943524,"about_ca_system_score_gemma":0.1463231,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9957014,"about_ca_topic_score_gemma":0.9944273,"domain_scores_codex":[0.9950745,0.0002886073,0.0006069859,0.0005602678,0.00227164,0.0011981],"domain_scores_gemma":[0.953652,0.001697937,0.001334804,0.001105932,0.03996211,0.002247177],"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":[0.00002179588,0.000008322826,0.00107237,0.0002417479,0.00001491971,0.000005294787,0.00002403739,0.00006872464,0.000006866538,0.0002035706,0.9970753,0.001257008],"study_design_scores_gemma":[0.0002432713,0.00001818141,0.04854225,0.001105723,0.00009369377,0.00002511902,0.0008218341,0.0003557709,0.0001846808,0.0004924637,0.948013,0.0001039585],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005549645,0.00003946243,0.00001450877,0.0001007903,0.00002069454,0.00001616839,0.9989659,0.00003773267,0.0007493704],"genre_scores_gemma":[0.0008909966,0.0002788063,0.0003431452,0.0002016128,0.00001899149,0.0001716983,0.9932476,0.00008169217,0.00476549],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08858884,"threshold_uncertainty_score":0.4312349,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05111910267299132,"score_gpt":0.2656846106649037,"score_spread":0.2145655079919124,"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."}}