{"id":"W4393550057","doi":"10.5281/zenodo.7572117","title":"Synthetic population for Canada at the DA level for 2016, 2021, 2023 and 2030.","year":2023,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Health, Environment, Cognitive Aging","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"UK Research and Innovation","keywords":"Geography; Environmental science","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":["sts","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001354213,0.0002456616,0.0002124407,0.00008130992,0.003245824,0.0003056446,0.0008064361,0.0001077043,0.0105183],"category_scores_gemma":[0.001378504,0.0002241439,0.00005101861,0.0002704779,0.0002322435,0.0001379565,0.001864422,0.0002802646,0.009774639],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009197047,"about_ca_system_score_gemma":0.0000126593,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.06470292,"about_ca_topic_score_gemma":0.0196589,"domain_scores_codex":[0.9974116,0.000300224,0.0003316336,0.0008482421,0.0005357149,0.0005725898],"domain_scores_gemma":[0.9985819,0.0002560112,0.0002150812,0.0006838498,0.00005207849,0.0002111166],"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":[0.00003082861,0.00002085807,0.000006459215,0.00009877681,0.00002330992,0.000003686699,0.0000406544,0.00009586464,0.0000700462,0.000007947007,0.981539,0.01806259],"study_design_scores_gemma":[0.0003233012,0.00009302378,0.002141354,0.00004728526,0.00004451616,0.00001745498,0.00009083041,0.0002819629,0.0000185128,0.00006899823,0.9966227,0.0002500404],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001024536,0.00005550401,0.000527567,0.001865702,0.0002406131,0.002225647,0.9930431,0.00007558976,0.0009416998],"genre_scores_gemma":[0.0009923453,0.0004143735,0.00008086797,0.0004975227,0.0001915317,0.000002109907,0.9899064,0.001017193,0.006897683],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.04504403,"threshold_uncertainty_score":0.9982298,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04787565714927019,"score_gpt":0.2597992486213467,"score_spread":0.2119235914720765,"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."}}