{"id":"W4206536099","doi":"10.1093/jamiaopen/ooab115","title":"Patients’, pharmacists’, and prescribers’ attitude toward using blockchain and machine learning in a proposed ePrescription system: online survey","year":2022,"lang":"en","type":"article","venue":"JAMIA Open","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Authorization; Medical prescription; Blockchain; Matching (statistics); Inclusion (mineral); Pharmacist; Reliability (semiconductor); Medicine; Computer security; Population; Computer science; Internet privacy; Family medicine; Medical emergency; Psychology; Pharmacy; Nursing; Social psychology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006204884,0.0001805738,0.000391708,0.0009372592,0.0005584182,0.00105563,0.0002777154,0.001009992,0.002873262],"category_scores_gemma":[0.01735064,0.0003536317,0.0007324098,0.0007549382,0.0006001276,0.001496482,0.0009611076,0.001072973,0.0006109626],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004648307,"about_ca_system_score_gemma":0.0006800651,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001561438,"about_ca_topic_score_gemma":0.001520065,"domain_scores_codex":[0.9954225,0.002095045,0.0007593844,0.0002763741,0.0009972894,0.0004494958],"domain_scores_gemma":[0.9822061,0.006173696,0.007152999,0.0005674543,0.001924078,0.001975606],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001504574,0.0005114129,0.9881648,0.00009490107,0.00006004918,0.0001312557,0.002876727,0.0001987209,0.0003087645,0.00005858479,0.0005338649,0.006910435],"study_design_scores_gemma":[0.00005249691,0.001558345,0.9755142,0.0001320893,0.0000653139,0.0009543846,0.0158316,0.002121586,0.0004195431,0.00007240119,0.003223785,0.00005409567],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9985684,0.0000834249,0.0001388829,0.0003555693,0.00000555034,0.00005201077,0.0001422064,0.000003585336,0.0006503418],"genre_scores_gemma":[0.9988365,0.0001876746,0.0002888685,0.0002759554,0.000010979,0.00005184534,0.0001051761,0.000001739428,0.0002413522],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006204884,"threshold_uncertainty_score":0.03281498,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2178504260748328,"score_gpt":0.4390055888750971,"score_spread":0.2211551628002643,"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."}}