{"id":"W2419250362","doi":"10.24095/hpcdp.34.4.12","title":"Chronic Disease and Injury Indicator Framework: Quick Stats, Fall 2014 Edition","year":2014,"lang":"en","type":"article","venue":"Chronic diseases and injuries in Canada","topic":"Healthcare Systems and Practices","field":"Health Professions","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medicine; Forensic engineering; Computer science; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000516422,0.000253428,0.0004022326,0.0001020929,0.0006720574,0.00003892128,0.0001587467,0.0001542466,0.0008007726],"category_scores_gemma":[0.0005887478,0.0002276865,0.00003127704,0.000124605,0.0001756345,0.0003690995,0.0001725948,0.0006806511,0.00002375607],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001866498,"about_ca_system_score_gemma":0.01293423,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6479301,"about_ca_topic_score_gemma":0.8401153,"domain_scores_codex":[0.9969884,0.0007835191,0.0006272845,0.0004807184,0.0003565507,0.000763515],"domain_scores_gemma":[0.9970747,0.001154229,0.0003240774,0.0004298917,0.00005939871,0.0009576858],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002621704,0.00004258932,0.6912385,0.00588727,0.00005696743,0.00002006658,0.0006112009,0.000006576186,0.000004291869,0.02273329,0.2020082,0.07712888],"study_design_scores_gemma":[0.0004621381,0.0001785744,0.327782,0.0007785658,0.00004172624,4.510973e-7,0.0008188636,0.0002163619,9.29611e-7,0.00253647,0.66691,0.0002739487],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9105803,0.0649754,0.0002034429,0.0148114,0.004242581,0.001649296,0.002086895,0.00009589244,0.001354737],"genre_scores_gemma":[0.9900427,0.004933325,0.00002784271,0.002095978,0.002367694,0.000231384,0.00008668453,0.00003548737,0.0001788652],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4649018,"threshold_uncertainty_score":0.9926615,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01907686996136965,"score_gpt":0.3735054098600255,"score_spread":0.3544285398986559,"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."}}