{"id":"W6977002507","doi":"10.6068/dp14ba826fb7546","title":"Most Recent Data (2000). Statistics Canada. CANSIM: Health - Health Care Services | Country: Canada | Table: Unmet health care needs, by age group and sex, household population aged 12 and over | Variable: 45 to 64 years, Males, Health care needs, not stated | Units: , 2000. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-112.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Health care; Health statistics; Census; Population; Official statistics; Socioeconomic status; Medical statistics; Medical prescription","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":[0.003026901,0.002592418,0.002885225,0.008272807,0.003694218,0.005350451,0.005632885,0.001798339,0.1152312],"category_scores_gemma":[0.02501452,0.001949863,0.002558889,0.0441588,0.0007155096,0.002381805,0.002596171,0.003550113,0.06059377],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.06876208,"about_ca_system_score_gemma":0.1615541,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9954363,"about_ca_topic_score_gemma":0.9933129,"domain_scores_codex":[0.9946156,0.0003658134,0.0006414415,0.0005596452,0.002588453,0.001229073],"domain_scores_gemma":[0.9526291,0.002078511,0.001231224,0.001163394,0.04038887,0.002508832],"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":[0.00002004023,0.000007429012,0.0007308206,0.0002652344,0.00001574613,0.000004995133,0.00001902121,0.00008845401,0.000006060307,0.0002481476,0.9972003,0.001393766],"study_design_scores_gemma":[0.0002433514,0.00001688873,0.03080439,0.001248758,0.00008805372,0.00002762159,0.0005815704,0.0004894704,0.0001582063,0.0006975585,0.9655293,0.0001148207],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004073846,0.00004520376,0.00001598943,0.0001362072,0.00002413538,0.00001690674,0.9987881,0.00004568081,0.0008871369],"genre_scores_gemma":[0.0008936395,0.0003002615,0.0004323444,0.0002487345,0.00002070102,0.0001774125,0.9934605,0.0001094352,0.004356805],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1152312,"threshold_uncertainty_score":0.4989061,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02807407451622801,"score_gpt":0.2650457436591405,"score_spread":0.2369716691429125,"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."}}