{"id":"W7026592638","doi":"","title":"Analysis of injury and fall hospitalization and associated risk factors among older adults in Saskatchewan, Canada, 1995/96 – 2004/05.","year":2010,"lang":"en","type":"dissertation","venue":"oURspace (University of Regina)","topic":"Adversarial Robustness in Machine Learning","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Ministry of Health, Saskatchewan; University of Regina","keywords":"Poison control; Risk factor; MEDLINE; Occupational safety and health; Injury prevention; Incidence (geometry); Human factors and ergonomics; Population","routes":{"ca_aff":false,"ca_fund":true,"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":[0.0002468303,0.0002385125,0.0006081472,0.0007416992,0.0001528029,0.00002785233,0.000472259,0.0004000599,0.000002175653],"category_scores_gemma":[0.0001384747,0.0003057994,0.00009372301,0.001215813,0.0001135351,0.0004601634,0.0001268938,0.0005238393,7.664162e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001643285,"about_ca_system_score_gemma":0.0003416359,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.3629418,"about_ca_topic_score_gemma":0.9846331,"domain_scores_codex":[0.9986663,0.0001521546,0.00004715622,0.0005056094,0.0004086608,0.0002200812],"domain_scores_gemma":[0.9981967,0.0001199877,0.001007471,0.0003439148,0.0002272946,0.0001046654],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004157802,0.0000355507,0.9728054,0.0001170829,0.0005396752,0.00002416853,0.01430548,0.003255153,0.00001888509,0.00008303476,0.004769529,0.004004402],"study_design_scores_gemma":[0.0004689331,0.00005435726,0.9320402,0.0001971555,0.0005290079,1.59824e-7,0.02506849,0.04085097,0.00001299829,0.00000339637,0.000489724,0.0002846737],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9893668,0.00007422649,0.006546498,0.003551336,0.0001793801,0.0001776238,0.00005050925,0.00002639563,0.00002719691],"genre_scores_gemma":[0.9910336,0.0000811089,0.001128935,0.000003333253,0.000005942936,2.225107e-7,0.0002366371,0.00001467105,0.00749552],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6216913,"threshold_uncertainty_score":0.9999394,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002397952734744002,"score_gpt":0.188001230109257,"score_spread":0.185603277374513,"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."}}