{"id":"W4408011571","doi":"10.31586/gjmcr.2023.1289","title":"Leveraging AI, ML, and Generative Neural Models to Bridge Gaps in Genetic Therapy Access and Real-Time Resource Allocation","year":2023,"lang":"en","type":"article","venue":"Global Journal of Medical Case Reports","topic":"Biomedical and Engineering Education","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Optech (Canada)","funders":"","keywords":"Bridge (graph theory); Computer science; Generative grammar; Resource allocation; Resource (disambiguation); Artificial intelligence; Machine learning; Medicine; Computer network; Internal medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006451651,0.0001164804,0.0002008194,0.0001318689,0.00003009122,0.00005931966,0.00006514333,0.0001061715,0.00001156687],"category_scores_gemma":[0.00008819171,0.00009902979,0.00002559701,0.0003833842,0.00003400067,0.0001541199,0.00004937611,0.0001964928,8.595172e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000836775,"about_ca_system_score_gemma":0.00006594519,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001692373,"about_ca_topic_score_gemma":0.00001280392,"domain_scores_codex":[0.9987001,0.0000360575,0.0004229139,0.0001451736,0.0004915961,0.0002041816],"domain_scores_gemma":[0.999339,0.00003995154,0.00006144756,0.00009323219,0.00004767801,0.0004187062],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009123895,0.0001219541,0.007168885,0.0004501831,0.0001910959,0.1595316,0.003548144,0.2472372,0.002786767,0.0000638122,0.05720215,0.5216069],"study_design_scores_gemma":[0.001064431,0.0001783563,0.1505066,0.0005474191,0.00003523476,0.2159906,0.0001761249,0.6254961,0.0002367471,0.001793277,0.003513162,0.0004620117],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9914799,0.001011954,0.003408507,0.003592345,0.0003080478,0.00008355422,0.000001957663,0.00005311356,0.00006058469],"genre_scores_gemma":[0.9978569,0.001381324,0.0002629027,0.0002209789,0.0002504757,0.000004542061,0.000004464307,0.00001218733,0.000006192301],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5211449,"threshold_uncertainty_score":0.4038318,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02954319826877667,"score_gpt":0.2982935775827674,"score_spread":0.2687503793139907,"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."}}