{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":35,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":35,"direct_label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline (scores rank; they never assert a category)","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12","author_layer_release":"2026-06-26"},"query_hash":"c59f4a1118cf","filters":{"venue":"JAMIA Open"}},"results":[{"id":"W3135275361","doi":"10.1093/jamiaopen/ooab012","title":"Evaluating the utility of synthetic COVID-19 case data","year":2021,"lang":"en","type":"article","venue":"JAMIA Open","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":43,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true},"ca_institutions":"Children's Hospital of Eastern Ontario; University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada; Compute Canada","keywords":"Proxy (statistics); Confidence interval; Synthetic data; Computer science; Missing data; Data mining; Coronavirus disease 2019 (COVID-19); Data set; Comorbidity; Statistics; Medicine; Artificial intelligence; Machine learning; Mathematics; Internal medicine","authors":[{"name":"Khaled El Emam","is_ca":true},{"name":"Lucy Mosquera","is_ca":false},{"name":"Elizabeth Jonker","is_ca":true},{"name":"Harpreet Sood","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.3792201548995654,"gpt":0.4740288269975024,"spread":0.09480867209793703,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.02238678,0.0007064373,0.0005598852,0.001739262,0.0005888761,0.001541836,0.001573618,0.001084044,0.001059136],"category_scores_gemma":[0.07845894,0.0003429433,0.001177108,0.001506519,0.000973535,0.0009787887,0.001359742,0.0009232461,0.0002196016],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00405479,"about_ca_system_score_gemma":0.001969669,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03634689,"about_ca_topic_score_gemma":0.02086728,"domain_scores_codex":[0.9910768,0.005499236,0.0007055934,0.001226061,0.001304632,0.0001876512],"domain_scores_gemma":[0.9088908,0.07354613,0.004344032,0.006487003,0.005987553,0.0007444368],"domain_codex":null,"domain_gemma":"reproducibility","domain_candidate":"reproducibility","domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003381015,0.0008457836,0.4497217,0.001090984,0.001777662,0.0006604236,0.000782175,0.4573585,0.001965418,0.004926236,0.00875824,0.06873196],"study_design_scores_gemma":[0.0004975165,0.001321241,0.09118453,0.0002304376,0.0004120615,0.0005636484,0.00110009,0.8868519,0.004328304,0.00641681,0.006998945,0.00009448071],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9607123,0.0007866356,0.02021644,0.001374409,0.0001079206,0.0005307902,0.01375647,0.0003954215,0.002119614],"genre_scores_gemma":[0.9704682,0.0001591693,0.01571343,0.000132003,0.00002871723,0.0001863305,0.01305993,0.00002008979,0.0002322448],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9776132,"threshold_uncertainty_score":0.118394,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4304208350","doi":"10.1093/jamiaopen/ooac083","title":"Validating a membership disclosure metric for synthetic health data","year":2022,"lang":"en","type":"article","venue":"JAMIA Open","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":38,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true},"ca_institutions":"Children's Hospital of Eastern Ontario; University of Ottawa","funders":"Canadian Institutes of Health Research","keywords":"Synthetic data; Metric (unit); Computer science; Benchmark (surveying); Population; Data mining; Generative model; Measure (data warehouse); Fraction (chemistry); Parametrization (atmospheric modeling); Sampling (signal processing); Ground truth; Machine learning; Generative grammar; Artificial intelligence; Geography; Medicine","authors":[{"name":"Khaled El Emam","is_ca":true},{"name":"Lucy Mosquera","is_ca":true},{"name":"Xi Fang","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1772611440591591,"gpt":0.3833628589269482,"spread":0.2061017148677891,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0287102,0.0007835194,0.0005969159,0.001214748,0.0008189225,0.001671072,0.00164592,0.001785685,0.000993193],"category_scores_gemma":[0.1063014,0.0002608011,0.0007124124,0.0008480089,0.00293181,0.002349365,0.002885741,0.001933377,0.0001825195],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00272515,"about_ca_system_score_gemma":0.001627637,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001372951,"about_ca_topic_score_gemma":0.0008289851,"domain_scores_codex":[0.982942,0.0110569,0.000745902,0.001642026,0.00318403,0.0004291213],"domain_scores_gemma":[0.8821571,0.08916667,0.007569976,0.01619253,0.003933146,0.0009807032],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007526518,0.0002540756,0.03268949,0.0002730667,0.0001925869,0.0001532157,0.0005190556,0.877496,0.004621266,0.02955252,0.002354435,0.05114171],"study_design_scores_gemma":[0.00004402576,0.0004174038,0.004615332,0.00007216944,0.00002701053,0.0002737785,0.0001194144,0.9583868,0.009434548,0.02527406,0.00130042,0.00003502843],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5142393,0.0007648906,0.4763696,0.002271696,0.0001262185,0.0005598853,0.001392608,0.0006512236,0.003624671],"genre_scores_gemma":[0.9573352,0.00008521627,0.04136573,0.0001665018,0.00002234262,0.0001352561,0.0006363096,0.0000239752,0.000229375],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0287102,"threshold_uncertainty_score":0.1518359,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4415259594","doi":"10.1093/jamiaopen/ooaf122","title":"ECG-FM: an open electrocardiogram foundation model","year":2025,"lang":"en","type":"article","venue":"JAMIA Open","topic":"ECG Monitoring and Analysis","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Vector Institute; University of Toronto; University Health Network","funders":"","keywords":"Foundation (evidence); Benchmark (surveying); Model validation; Mathematical model","authors":[{"name":"Kaden McKeen","is_ca":true},{"name":"Sameer Masood","is_ca":true},{"name":"Augustin Toma","is_ca":true},{"name":"Barry Rubin","is_ca":true},{"name":"Bo Wang","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04183354412196715,"gpt":0.4110970820647269,"spread":0.3692635379427597,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00110117,0.0007310034,0.0004751386,0.0005154219,0.0002258894,0.0006748488,0.001957412,0.001030614,0.003590894],"category_scores_gemma":[0.00437291,0.0004175175,0.0009431604,0.0002570434,0.0003500473,0.0009050666,0.001246291,0.001503704,0.001422415],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006030159,"about_ca_system_score_gemma":0.001259415,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004570027,"about_ca_topic_score_gemma":0.007491542,"domain_scores_codex":[0.9996694,0.00007300328,0.00001842249,0.0001146148,0.00008681798,0.00003763942],"domain_scores_gemma":[0.9993088,0.0002960362,0.00006033627,0.0001276251,0.0001518567,0.00005537855],"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":[0.00105449,0.0004062703,0.01074233,0.0003331937,0.0002930294,0.0004661907,0.0001459856,0.4143153,0.01760733,0.01472134,0.04083614,0.4990784],"study_design_scores_gemma":[0.00004919207,0.000128457,0.001015758,0.00002941528,0.00002333309,0.0001514883,0.00001015419,0.9859405,0.00280549,0.005537598,0.004290192,0.00001853131],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04285758,0.0007167725,0.9366874,0.000911856,0.0002763425,0.0002473651,0.00332096,0.01180763,0.003174107],"genre_scores_gemma":[0.5864161,0.0007462663,0.3876932,0.001144276,0.0002496958,0.0006730275,0.012852,0.001283023,0.008942442],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004570027,"threshold_uncertainty_score":0.01201272,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3153295646","doi":"10.1093/jamiaopen/ooab018","title":"EHR “SWAT” teams: a physician engagement initiative to improve Electronic Health Record (EHR) experiences and mitigate possible causes of EHR-related burnout","year":2021,"lang":"en","type":"article","venue":"JAMIA Open","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":25,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health","funders":"","keywords":"Informatics; Pharmacy; Burnout; Electronic health record; Health information technology; Health informatics; Medicine; Medical education; Health care; Nursing; Knowledge management; Computer science; Public health; Engineering","authors":[{"name":"Lydia Sequeira","is_ca":true},{"name":"Khaled Almilaji","is_ca":true},{"name":"Gillian Strudwick","is_ca":true},{"name":"Damian Jankowicz","is_ca":true},{"name":"Tania Tajirian","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.05065751252028157,"gpt":0.4242902656007245,"spread":0.373632753080443,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005756392,0.0004875578,0.0001981443,0.0006773595,0.005474769,0.002448614,0.001082888,0.001750236,0.003382381],"category_scores_gemma":[0.01119746,0.0003507573,0.000585943,0.0004055488,0.001797541,0.002040429,0.00667837,0.00238715,0.0008900249],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001372199,"about_ca_system_score_gemma":0.005350709,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00123331,"about_ca_topic_score_gemma":0.004135046,"domain_scores_codex":[0.9894431,0.006899794,0.0003567219,0.0005416028,0.001274547,0.001484302],"domain_scores_gemma":[0.9882396,0.002666429,0.001846904,0.0007244736,0.0009120613,0.005610495],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0006723358,0.0118357,0.1176419,0.0009569325,0.000122532,0.01246705,0.1725637,0.001207499,0.01451834,0.006079925,0.06708321,0.5948508],"study_design_scores_gemma":[0.0007565194,0.02237224,0.1284977,0.001652166,0.0002834962,0.03892393,0.3144866,0.01223855,0.02302706,0.01096488,0.4462919,0.0005050743],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9025454,0.0005036341,0.04015168,0.03010681,0.0005632489,0.0008539493,0.00009162024,0.00095138,0.02423223],"genre_scores_gemma":[0.9337397,0.0004343184,0.04956863,0.008695682,0.0003458415,0.0005765231,0.0001398176,0.0001385702,0.006360943],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005756392,"threshold_uncertainty_score":0.03044307,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"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,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"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","authors":[{"name":"Bader Aldughayfiq","is_ca":true},{"name":"Srinivas Sampalli","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.2178504260748328,"gpt":0.4390055888750971,"spread":0.2211551628002643,"validation_status":"score_only:v0-immature-baseline"},"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"},"labels":[],"label_agreement":null},{"id":"W4404414807","doi":"10.1093/jamiaopen/ooae108","title":"Addressing ethical issues in healthcare artificial intelligence using a lifecycle-informed process","year":2024,"lang":"en","type":"article","venue":"JAMIA Open","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Simon Fraser University","funders":"U.S. National Library of Medicine; National Human Genome Research Institute; National Institutes of Health","keywords":"Deliberation; System lifecycle; Context (archaeology); Process (computing); Engineering ethics; Knowledge management; Health care; Application lifecycle management; Management science; Computer science; Engineering; Political science; Politics","authors":[{"name":"Benjamin Collins","is_ca":false},{"name":"Jean‐Christophe Bélisle‐Pipon","is_ca":true},{"name":"Barbara J. Evans","is_ca":false},{"name":"Kadija Ferryman","is_ca":false},{"name":"Xiaoqian Jiang","is_ca":false},{"name":"Camille Nebeker","is_ca":false},{"name":"Laurie L. Novak","is_ca":false},{"name":"Kirk Roberts","is_ca":false},{"name":"Martin C. Were","is_ca":false},{"name":"Zhijun Yin","is_ca":false},{"name":"Vardit Ravitsky","is_ca":false},{"name":"Joseph Coco","is_ca":false},{"name":"Rachele Hendricks‐Sturrup","is_ca":false},{"name":"Ishan C. Williams","is_ca":false},{"name":"Ellen Wright Clayton","is_ca":false},{"name":"Bradley Malin","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.5427085924048283,"gpt":0.6096807545039306,"spread":0.06697216209910228,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.1567878,0.001454165,0.0008967081,0.005443058,0.01059947,0.02234106,0.003903822,0.008292292,0.00423609],"category_scores_gemma":[0.1334611,0.001162397,0.002228756,0.003680976,0.04069437,0.02040751,0.01818729,0.0110869,0.00127138],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01650174,"about_ca_system_score_gemma":0.05800465,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00400222,"about_ca_topic_score_gemma":0.005301822,"domain_scores_codex":[0.8155283,0.1556016,0.006539324,0.0038716,0.01581133,0.002647849],"domain_scores_gemma":[0.7909783,0.1561072,0.01253753,0.01538032,0.02085961,0.004137019],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00004812409,0.0001794941,0.002071166,0.000973116,0.00005516564,0.0006867925,0.08242507,0.003613407,0.0009164754,0.8289397,0.005318331,0.07477315],"study_design_scores_gemma":[0.00005351377,0.00008711917,0.0006250197,0.003051147,0.00004036932,0.0005535539,0.03462815,0.00759041,0.001459589,0.8366913,0.1151328,0.00008707549],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02291398,0.003623043,0.7838202,0.08761857,0.0005078604,0.00559917,0.0001538931,0.0003179804,0.09544534],"genre_scores_gemma":[0.3078647,0.002812309,0.6746945,0.004639739,0.0002268567,0.003286747,0.0002138228,0.0001297133,0.006131553],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1567878,"threshold_uncertainty_score":0.829183,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3191558428","doi":"10.1093/jamiaopen/ooab050","title":"Smart About Meds (SAM): a pilot randomized controlled trial of a mobile application to improve medication adherence following hospital discharge","year":2021,"lang":"en","type":"article","venue":"JAMIA Open","topic":"Medication Adherence and Compliance","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"McGill University Health Centre; University of Toronto; McGill University","funders":"Ministère de l'Économie, de la Science et de l'Innovation - Québec","keywords":"Medicine; Randomized controlled trial; Pharmacy; Emergency medicine; Randomization; Emergency department; Adverse effect; Intervention (counseling); Hospital discharge; Physical therapy; Internal medicine; Family medicine; Nursing","authors":[{"name":"Bettina Habib","is_ca":true},{"name":"David L. Buckeridge","is_ca":true},{"name":"Melissa Bustillo","is_ca":true},{"name":"Santiago Nicolas Marquez","is_ca":true},{"name":"Manish Thakur","is_ca":true},{"name":"Thai Hoa Tran","is_ca":true},{"name":"Daniala L. Weir","is_ca":true},{"name":"Robyn Tamblyn","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.0171226190008465,"gpt":0.3304506051629214,"spread":0.3133279861620749,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003887663,0.001277103,0.0018582,0.0006202006,0.0005926306,0.0008041031,0.0009796274,0.001643879,0.006454444],"category_scores_gemma":[0.005812019,0.0005859894,0.001812512,0.0004318575,0.001307628,0.001028799,0.0007669909,0.001885047,0.0004234783],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007230183,"about_ca_system_score_gemma":0.001920048,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001285335,"about_ca_topic_score_gemma":0.001928224,"domain_scores_codex":[0.9974596,0.00169918,0.0002424056,0.0002357693,0.000147345,0.0002157562],"domain_scores_gemma":[0.9964283,0.001673494,0.0008131895,0.000211167,0.0002084014,0.0006655],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"randomized_trial","study_design_gemma":"randomized_trial","study_design_scores_codex":[0.9247923,0.0424851,0.001908668,0.001488424,0.0008700752,0.00007544277,0.0002006701,0.0002641708,0.001562081,0.0001699957,0.0008507401,0.02533242],"study_design_scores_gemma":[0.7922137,0.2033429,0.0029059,0.00005614587,0.0003396996,0.00001606693,0.00005399429,0.0003344621,0.0003126496,0.00007192538,0.0003414229,0.00001107221],"study_design_candidate":"randomized_trial","study_design_consensus":"randomized_trial","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.978833,0.000797493,0.0006227159,0.0006453514,0.0004200565,0.01725526,0.0004748792,0.0001078451,0.000843416],"genre_scores_gemma":[0.9629488,0.0007450772,0.004378647,0.000870425,0.0005095115,0.02896341,0.0003507286,0.00001106058,0.001222318],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006454444,"threshold_uncertainty_score":0.02159226,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2897257082","doi":"10.1093/jamiaopen/ooy044","title":"Improving inpatient mental health medication safety through the process of obtaining HIMSS Stage 7: a case report","year":2018,"lang":"en","type":"article","venue":"JAMIA Open","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":14,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"Centre for Addiction and Mental Health","funders":"","keywords":"Stage (stratigraphy); Process (computing); Mental health; Medicine; Patient safety; Operations management; Political science; Engineering; Psychiatry; Computer science; Geology; Health care","authors":[{"name":"Heather Sulkers","is_ca":true},{"name":"Tania Tajirian","is_ca":true},{"name":"Jane Paterson","is_ca":true},{"name":"Daniela Mucuceanu","is_ca":true},{"name":"Tracey MacArthur","is_ca":true},{"name":"John S. Strauss","is_ca":true},{"name":"Kamini Kalia","is_ca":true},{"name":"Gillian Strudwick","is_ca":true},{"name":"Damian Jankowicz","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.07512779135518617,"gpt":0.4968540639458993,"spread":0.4217262725907132,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001836513,0.001475484,0.0006020651,0.002442164,0.00673763,0.003396772,0.002602701,0.00640852,0.002207548],"category_scores_gemma":[0.01731122,0.0009439363,0.00166138,0.001906411,0.003055567,0.003090629,0.004659219,0.008388581,0.0006292555],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006851217,"about_ca_system_score_gemma":0.005889927,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02813576,"about_ca_topic_score_gemma":0.04937783,"domain_scores_codex":[0.9941245,0.001653967,0.0007464014,0.0003714961,0.001520727,0.001583018],"domain_scores_gemma":[0.990772,0.004071513,0.002181141,0.0004752669,0.0007732312,0.001726829],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"case_report","study_design_gemma":"case_report","study_design_scores_codex":[0.00002600407,0.0004159195,0.02172561,0.0001005114,0.00002180635,0.9427421,0.01654622,0.0003428872,0.0005773563,0.00531793,0.002549138,0.00963451],"study_design_scores_gemma":[0.00001099351,0.0001804063,0.006902582,0.0002767508,0.00004215134,0.9602714,0.01865799,0.001932096,0.002041679,0.001429018,0.00819515,0.00005988638],"study_design_candidate":"case_report","study_design_consensus":"case_report","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9113113,0.002240605,0.01099261,0.03166172,0.0006013553,0.0007469837,0.0002163304,0.0002439311,0.04198521],"genre_scores_gemma":[0.973525,0.003064382,0.009442613,0.005577662,0.0006732229,0.0001573255,0.0001496876,0.00007833585,0.007331807],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02813576,"threshold_uncertainty_score":0.05594397,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4409347038","doi":"10.1093/jamiaopen/ooaf021","title":"A proof-of-concept study for patient use of open notes with large language models","year":2025,"lang":"en","type":"article","venue":"JAMIA Open","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":14,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Guelph","funders":"Patrick J. McGovern Foundation","keywords":"Proof of concept; Computer science; Programming language","authors":[{"name":"Liz Salmi","is_ca":false},{"name":"Dana Lewis","is_ca":false},{"name":"Jennifer Clarke","is_ca":false},{"name":"Rudy Fischmann","is_ca":false},{"name":"Emily I. McIntosh","is_ca":true},{"name":"Chethan Sarabu","is_ca":false},{"name":"Catherine M. DesRoches","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1340610295313068,"gpt":0.491993353790721,"spread":0.3579323242594141,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.09792682,0.001877324,0.001240149,0.0008187032,0.001094907,0.002678724,0.00273851,0.002750848,0.008779556],"category_scores_gemma":[0.1332595,0.0008656654,0.00193216,0.0004360255,0.002369786,0.002867,0.002344643,0.002789532,0.001403583],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001207086,"about_ca_system_score_gemma":0.006598293,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004349774,"about_ca_topic_score_gemma":0.0004172846,"domain_scores_codex":[0.9385183,0.0476344,0.003311094,0.002338363,0.006914031,0.001283699],"domain_scores_gemma":[0.7999656,0.1440481,0.01630234,0.01326769,0.02212224,0.004294101],"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":[0.1044381,0.1824838,0.02505353,0.03398067,0.002662437,0.00279352,0.0276115,0.007466711,0.1040576,0.01423303,0.02007393,0.4751452],"study_design_scores_gemma":[0.05199387,0.7401376,0.01451456,0.004305501,0.001873979,0.001892549,0.005852173,0.008749371,0.1043003,0.003847965,0.06217368,0.0003584911],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7393898,0.001817783,0.1024333,0.00206692,0.001106694,0.1447625,0.002143385,0.0007211285,0.005558503],"genre_scores_gemma":[0.5986598,0.001156331,0.282413,0.001810308,0.0003943999,0.1121526,0.0006865372,0.0001500341,0.002577042],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09792682,"threshold_uncertainty_score":0.5178927,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3011970739","doi":"10.1093/jamiaopen/ooz071","title":"National monitoring and evaluation of eHealth: a scoping review","year":2020,"lang":"en","type":"review","venue":"JAMIA Open","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":13,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"Aalborg Universitet","keywords":"eHealth; Benchmarking; Monitoring and evaluation; Grey literature; Business; Computer science; Health care; MEDLINE; Political science; Marketing","authors":[{"name":"Sidsel Villumsen","is_ca":false},{"name":"Julia Adler‐Milstein","is_ca":false},{"name":"Christian Nøhr","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.5755180814473538,"gpt":0.6684052257289647,"spread":0.09288714428161082,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.1295848,0.001838075,0.006986886,0.04053323,0.002539585,0.00980632,0.004091603,0.003740991,0.005558398],"category_scores_gemma":[0.3306892,0.001789478,0.006723795,0.03872112,0.003199005,0.01156097,0.007256791,0.003202731,0.001124604],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01342447,"about_ca_system_score_gemma":0.06815329,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01478637,"about_ca_topic_score_gemma":0.02013055,"domain_scores_codex":[0.8860567,0.040394,0.0457916,0.003745813,0.0224799,0.001531972],"domain_scores_gemma":[0.6327931,0.2363461,0.04453411,0.009462652,0.07490071,0.001963299],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","study_design_scores_codex":[0.0001756765,0.00007974623,0.002999494,0.6135139,0.002162283,0.0001266093,0.001787487,0.0005232394,0.000223653,0.003618606,0.01009643,0.3646929],"study_design_scores_gemma":[0.00003566805,0.00005418191,0.00266644,0.9619783,0.00302349,0.00009294016,0.0008250283,0.0001599162,0.0001900889,0.0008255513,0.03012409,0.00002445613],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.001574153,0.9806326,0.00292573,0.004467511,0.0008629034,0.002787632,0.001439874,0.00006585965,0.005243719],"genre_scores_gemma":[0.01882922,0.9631687,0.009134885,0.001299057,0.0003396347,0.005260668,0.001539965,0.00003805786,0.0003898623],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.1295848,"threshold_uncertainty_score":0.6853183,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4312211804","doi":"10.1093/jamiaopen/ooac105","title":"OpenSep: a generalizable open source pipeline for SOFA score calculation and Sepsis-3 classification","year":2022,"lang":"en","type":"article","venue":"JAMIA Open","topic":"Sepsis Diagnosis and Treatment","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Institute for Clinical Evaluative Sciences; SickKids Foundation; Hospital for Sick Children","funders":"","keywords":"Sepsis; Pipeline (software); Generalizability theory; Computer science; Medicine; Reliability (semiconductor); SOFA score; Internal medicine; Statistics; Power (physics); Mathematics; Operating system","authors":[{"name":"Mackenzie Hofford","is_ca":false},{"name":"Sean Yu","is_ca":false},{"name":"Alistair E. W. Johnson","is_ca":true},{"name":"Albert M. Lai","is_ca":false},{"name":"Philip Payne","is_ca":false},{"name":"Andrew P. Michelson","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.2268574067430595,"gpt":0.405555724765615,"spread":0.1786983180225555,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006218112,0.002355687,0.001506749,0.007031022,0.001125021,0.003943488,0.002917863,0.001452285,0.02445772],"category_scores_gemma":[0.04336934,0.001483114,0.003069252,0.003996548,0.0006914522,0.003402498,0.007128037,0.002498287,0.02435184],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00124424,"about_ca_system_score_gemma":0.004911005,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006612868,"about_ca_topic_score_gemma":0.007413291,"domain_scores_codex":[0.9954887,0.0008053332,0.0007556118,0.001301568,0.00133642,0.0003122921],"domain_scores_gemma":[0.9859799,0.00702685,0.001362597,0.002382903,0.002642412,0.0006054575],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001888127,0.0002725142,0.03860106,0.004391756,0.001022451,0.001222557,0.001467625,0.007810873,0.007658738,0.01006151,0.6723904,0.2532124],"study_design_scores_gemma":[0.0005274119,0.0002783133,0.04251727,0.001483881,0.0004023239,0.001659291,0.0006929962,0.08953685,0.02599828,0.05796552,0.7782177,0.0007202043],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"software","genre_gemma":"methods","genre_scores_codex":[0.007689743,0.001011591,0.2511318,0.001312201,0.0004790138,0.00120421,0.2633774,0.4668582,0.006935797],"genre_scores_gemma":[0.06499162,0.001223746,0.2868091,0.001512947,0.0003764419,0.002779349,0.5873035,0.04861686,0.006386431],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.02445772,"threshold_uncertainty_score":0.08181924,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4385709848","doi":"10.1093/jamiaopen/ooad062","title":"Automated identification of unstandardized medication data: a scalable and flexible data standardization pipeline using RxNorm on GEMINI multicenter hospital data","year":2023,"lang":"en","type":"article","venue":"JAMIA Open","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true},"ca_institutions":"University of Toronto; St. Michael's Hospital","funders":"Alliance de recherche numérique du Canada","keywords":"Standardization; Computer science; Identifier; Pharmacy; Coding (social sciences); Data mining; Information retrieval; Medicine; Statistics; Mathematics; Family medicine","authors":[{"name":"Riley Waters","is_ca":true},{"name":"Sarah Malecki","is_ca":true},{"name":"Sharan Lail","is_ca":true},{"name":"Denise Mak","is_ca":true},{"name":"Sudipta Saha","is_ca":true},{"name":"Hae Young Jung","is_ca":true},{"name":"Mohammed Arshad Imrit","is_ca":true},{"name":"Fahad Razak","is_ca":true},{"name":"Amol A. Verma","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.09741173152302603,"gpt":0.4051766285713367,"spread":0.3077648970483107,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02291794,0.001665647,0.001127704,0.006035862,0.001097759,0.003496294,0.002256845,0.0006959593,0.001897202],"category_scores_gemma":[0.04283873,0.0008868027,0.001532432,0.004723921,0.001059669,0.004105562,0.004252796,0.001468244,0.001811263],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002627307,"about_ca_system_score_gemma":0.006855585,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01926284,"about_ca_topic_score_gemma":0.01506424,"domain_scores_codex":[0.9860137,0.003490947,0.002213792,0.003454697,0.004375889,0.0004510507],"domain_scores_gemma":[0.9682873,0.01021647,0.004793179,0.008882719,0.007109439,0.0007107822],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002162022,0.0006583183,0.140184,0.001460255,0.0007950412,0.001102731,0.003911375,0.02062934,0.04967035,0.00834034,0.08722878,0.6838574],"study_design_scores_gemma":[0.0006620859,0.0008763178,0.120377,0.000666213,0.0004134311,0.00147264,0.002450626,0.4801412,0.1960168,0.01717509,0.1791541,0.0005945335],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1334763,0.001609107,0.5519601,0.003147989,0.0001779025,0.002416237,0.04159261,0.2594373,0.006182528],"genre_scores_gemma":[0.2147084,0.0005385302,0.712531,0.0007375658,0.00009932744,0.0008361132,0.06495054,0.003678691,0.001919738],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02291794,"threshold_uncertainty_score":0.1212031,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3167370031","doi":"10.1093/jamiaopen/ooab035","title":"Aligning an interface terminology to the Logical Observation Identifiers Names and Codes (LOINC®)","year":2021,"lang":"en","type":"article","venue":"JAMIA Open","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":8,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université de Montréal; Centre Hospitalier de l’Université de Montréal","funders":"","keywords":"Identifier; Computer science; Interface (matter); Artificial intelligence; Terminology; Interoperability; Information retrieval; Programming language; World Wide Web","authors":[{"name":"Jean Noël Nikiema","is_ca":true},{"name":"Romain Griffier","is_ca":false},{"name":"Vianney Jouhet","is_ca":false},{"name":"Fleur Mougin","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.05609294620949171,"gpt":0.3524308735598511,"spread":0.2963379273503594,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009408455,0.0009270002,0.0006286147,0.00740471,0.0009475942,0.004153342,0.001222311,0.001048286,0.002695485],"category_scores_gemma":[0.02021856,0.0003968657,0.0009367124,0.00549898,0.001281722,0.00310597,0.002549794,0.001096147,0.001785505],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002978806,"about_ca_system_score_gemma":0.005072872,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009733411,"about_ca_topic_score_gemma":0.004316557,"domain_scores_codex":[0.9903267,0.003583094,0.002089372,0.001753317,0.001800034,0.0004474639],"domain_scores_gemma":[0.9823793,0.006375516,0.002945817,0.003381875,0.004484089,0.0004333856],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001921286,0.0004530624,0.1735369,0.005313992,0.0004018714,0.001781865,0.02626704,0.01213067,0.1344302,0.09323593,0.0302598,0.5202674],"study_design_scores_gemma":[0.000157718,0.000837826,0.1751127,0.001819247,0.0007563485,0.002916716,0.01376884,0.06376173,0.1520403,0.02922712,0.5592018,0.0003996745],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2419311,0.001467989,0.7199669,0.001199305,0.0005503651,0.0008787385,0.008569471,0.008687962,0.0167481],"genre_scores_gemma":[0.412366,0.000575045,0.5577679,0.0004269978,0.0001185449,0.0007465697,0.02183983,0.002523358,0.003635875],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009733411,"threshold_uncertainty_score":0.0497573,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3173464900","doi":"10.1093/jamiaopen/ooab037","title":"Smart about medications (SAM): a digital solution to enhance medication management following hospital discharge","year":2021,"lang":"en","type":"article","venue":"JAMIA Open","topic":"Medication Adherence and Compliance","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"McGill University Health Centre; McGill University","funders":"McGill University Health Centre; McGill University","keywords":"Usability; Workflow; System usability scale; Medicine; Scale (ratio); Medication therapy management; Pharmacist; Medical emergency; Computer science; Heuristic evaluation; Nursing; Database; Pharmacy; Human–computer interaction","authors":[{"name":"Santiago Márquez Fosser","is_ca":true},{"name":"Mahmoud Nadar","is_ca":true},{"name":"Bettina Habib","is_ca":true},{"name":"Daniala L. Weir","is_ca":true},{"name":"Fiona K.I. Chan","is_ca":true},{"name":"Rola El Halabieh","is_ca":true},{"name":"Jeanne Vachon","is_ca":true},{"name":"Manish Thakur","is_ca":true},{"name":"Thai Hoa Tran","is_ca":true},{"name":"Melissa Bustillo","is_ca":true},{"name":"Caroline Beauchamp","is_ca":true},{"name":"André Bonnici","is_ca":true},{"name":"David L. Buckeridge","is_ca":true},{"name":"Robyn Tamblyn","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01919696020667829,"gpt":0.3445249885931057,"spread":0.3253280283864274,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001442109,0.000386669,0.0003067194,0.0006751843,0.0002386923,0.0006724996,0.0005769642,0.0004719104,0.005085636],"category_scores_gemma":[0.005231335,0.0001826797,0.0004690516,0.0002771132,0.0001961091,0.0004932912,0.0008638157,0.0003625322,0.0009023026],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001742535,"about_ca_system_score_gemma":0.0006305066,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002303358,"about_ca_topic_score_gemma":0.0006305532,"domain_scores_codex":[0.9991792,0.000370988,0.0001196771,0.0000681247,0.0002087741,0.00005320484],"domain_scores_gemma":[0.9975122,0.00132902,0.0004344551,0.0001861033,0.0002740236,0.0002641923],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"nonrandomized_trial","study_design_scores_codex":[0.001062703,0.001701561,0.02072452,0.001548626,0.00008385572,0.0005510895,0.001280618,0.0004818036,0.01869377,0.0003589251,0.009950665,0.9435619],"study_design_scores_gemma":[0.004630057,0.06231021,0.5519639,0.003634698,0.001647635,0.01370772,0.004627254,0.02559326,0.09527414,0.003283319,0.2327777,0.0005501327],"study_design_candidate":"nonrandomized_trial","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8926236,0.003149156,0.06851433,0.003723113,0.0004314237,0.00338449,0.001582857,0.01203797,0.01455313],"genre_scores_gemma":[0.7140532,0.002380934,0.2708016,0.001791977,0.0002976521,0.002063443,0.001245211,0.0002341404,0.007131721],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005085636,"threshold_uncertainty_score":0.01701319,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4389102197","doi":"10.1093/jamiaopen/ooad094","title":"Tracking pregnant women’s mental health through social media: an analysis of reddit posts","year":2023,"lang":"en","type":"article","venue":"JAMIA Open","topic":"Mental Health via Writing","field":"Psychology","cited_by":8,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Manitoba; Manitoba Health","funders":"Canadian Institutes of Health Research","keywords":"Pandemic; Mental health; Anxiety; Social media; Depression (economics); Psychology; Stressor; Public health; Psychiatry; Social support; Coronavirus disease 2019 (COVID-19); Medicine; Social psychology; Computer science; Nursing; World Wide Web; Infectious disease (medical specialty)","authors":[{"name":"Abhishek Dhankar","is_ca":true},{"name":"Alan Katz","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1075871450039483,"gpt":0.4555206239093916,"spread":0.3479334789054432,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007190625,0.0003500855,0.0001656763,0.002081307,0.0002860536,0.0006458422,0.0002380065,0.0003727289,0.001267436],"category_scores_gemma":[0.004638684,0.0001136264,0.000282737,0.001210054,0.0001592984,0.0007156183,0.0005536004,0.0003985758,0.0008674746],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002590315,"about_ca_system_score_gemma":0.0002089072,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003319715,"about_ca_topic_score_gemma":0.005570403,"domain_scores_codex":[0.9996248,0.0001305107,0.00004503969,0.00007941388,0.0000779724,0.00004218862],"domain_scores_gemma":[0.9965776,0.002229243,0.0004681123,0.0001676558,0.0004008294,0.0001566411],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007421214,0.0003325343,0.7697875,0.0007776404,0.0001421603,0.001635944,0.009822384,0.001877453,0.01590844,0.000665325,0.01759362,0.1807149],"study_design_scores_gemma":[0.00001925222,0.0002626076,0.934754,0.0001302158,0.0001031002,0.00107848,0.007162756,0.03033508,0.00537537,0.0007887877,0.01994235,0.00004807563],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9748481,0.0004628933,0.003408266,0.0007027139,0.00009219417,0.0001648012,0.01656204,0.0003186928,0.003440286],"genre_scores_gemma":[0.9753659,0.0003973051,0.00828446,0.0001543736,0.0001230073,0.0002114503,0.01302603,0.00004025556,0.002397319],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003319715,"threshold_uncertainty_score":0.006600797,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3209059416","doi":"10.1093/jamiaopen/ooab100","title":"Dark clouds and silver linings: impact of COVID-19 on internet users’ privacy","year":2021,"lang":"en","type":"article","venue":"JAMIA Open","topic":"COVID-19 Digital Contact Tracing","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Calgary","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Internet privacy; Coronavirus disease 2019 (COVID-19); The Internet; 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Cloud computing; Computer science; Computer security; World Wide Web; Virology; Medicine; Infectious disease (medical specialty)","authors":[{"name":"Ram Gopal","is_ca":false},{"name":"Hooman Hidaji","is_ca":true},{"name":"Raymond A. Patterson","is_ca":true},{"name":"Niam Yaraghi","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.05315343417190545,"gpt":0.3578510670684957,"spread":0.3046976328965903,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005435283,0.0002108487,0.0003274666,0.0008547971,0.001033817,0.00333623,0.0009109514,0.0009369513,0.009803474],"category_scores_gemma":[0.04755233,0.0003158464,0.001152876,0.001248448,0.001740738,0.003171591,0.003269068,0.002934639,0.0007049479],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002029729,"about_ca_system_score_gemma":0.001963976,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02384407,"about_ca_topic_score_gemma":0.01729689,"domain_scores_codex":[0.9935348,0.003223424,0.0003480101,0.0007556189,0.001153974,0.0009842678],"domain_scores_gemma":[0.9409682,0.02376087,0.0230435,0.004174899,0.003699108,0.004353451],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001694113,0.000149486,0.9839427,0.00003972228,0.00008951545,0.00009337955,0.001597635,0.0007638426,0.0001064099,0.001546194,0.00118707,0.01031448],"study_design_scores_gemma":[0.000009289384,0.0001496645,0.9821569,0.0001327289,0.00005787622,0.000236359,0.006026581,0.006423364,0.0003404405,0.001878172,0.002555588,0.00003313656],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9902154,0.0003422903,0.001050561,0.003477665,0.0000323283,0.00002823314,0.0007594097,0.00003049919,0.004063601],"genre_scores_gemma":[0.9991195,0.00006692779,0.0001995326,0.0001355591,0.00001239512,0.000008176343,0.0001557971,0.000007293679,0.0002949072],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02384407,"threshold_uncertainty_score":0.04741055,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2810514665","doi":"10.1093/jamiaopen/ooy026","title":"Learning optimal opioid prescribing and monitoring: a simulation study of medical residents","year":2018,"lang":"en","type":"article","venue":"JAMIA Open","topic":"Simulation-Based Education in Healthcare","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"D-Wave Systems (Canada)","funders":"Agency for Healthcare Research and Quality","keywords":"Medicine; Opioid; (+)-Naloxone; Dosing; Physical therapy; Clinical trial; Emergency medicine; Internal medicine","authors":[{"name":"Thomas Kannampallil","is_ca":false},{"name":"Robert Mcnutt","is_ca":false},{"name":"Suzanne Falck","is_ca":false},{"name":"William Galanter","is_ca":false},{"name":"Dave Patterson","is_ca":true},{"name":"Houshang Darabi","is_ca":false},{"name":"Ashkan Sharabiani","is_ca":false},{"name":"Gordon D. Schiff","is_ca":false},{"name":"Richard Odwazny","is_ca":false},{"name":"Allen J. Vaida","is_ca":false},{"name":"Diana J. Wilkie","is_ca":false},{"name":"Bruce L. Lambert","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1003521309766349,"gpt":0.4633072391035065,"spread":0.3629551081268716,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004075542,0.0005991095,0.0004954842,0.0003598452,0.0006099644,0.0007698437,0.0007576008,0.001026814,0.001394836],"category_scores_gemma":[0.01119234,0.0006185586,0.0008207447,0.0002206028,0.0007124015,0.0007171746,0.0009073582,0.001272301,0.0002956683],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001203277,"about_ca_system_score_gemma":0.001920324,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003043611,"about_ca_topic_score_gemma":0.004018656,"domain_scores_codex":[0.9982565,0.001060698,0.000072581,0.0001447882,0.0001471529,0.0003181917],"domain_scores_gemma":[0.994013,0.002940435,0.0007087199,0.0005125818,0.00036742,0.001457837],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.02396563,0.362003,0.4990498,0.0002911403,0.0006660281,0.0007607944,0.01118649,0.03336253,0.007807854,0.0005909377,0.001454159,0.05886166],"study_design_scores_gemma":[0.006728427,0.4193072,0.4217304,0.0001539999,0.0003083593,0.0005907595,0.008903357,0.1282154,0.009422593,0.001325949,0.002997617,0.0003159628],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9997477,0.000007080848,0.0001149179,0.0000156958,0.000001862376,0.00004831928,0.00001191422,0.000002033051,0.00005041723],"genre_scores_gemma":[0.998248,0.00004045096,0.001143837,0.00004983597,0.0000106319,0.0002237689,0.00007758511,0.000001640944,0.0002042825],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004075542,"threshold_uncertainty_score":0.02155375,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4391055787","doi":"10.1093/jamiaopen/ooae001","title":"A platform for connecting social media data to domain-specific topics using large language models: an application to student mental health","year":2024,"lang":"en","type":"article","venue":"JAMIA Open","topic":"Mental Health via Writing","field":"Psychology","cited_by":6,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"Health Canada","keywords":"Social media; Computer science; Parsing; Theme (computing); Process (computing); Data science; Domain (mathematical analysis); Key (lock); Similarity (geometry); Human–computer interaction; World Wide Web; Natural language processing; Artificial intelligence; Information retrieval; Programming language","authors":[{"name":"Leonard Ruocco","is_ca":true},{"name":"Yuqian Zhuang","is_ca":true},{"name":"Raymond T. Ng","is_ca":true},{"name":"Richard J. Munthali","is_ca":true},{"name":"Kristen L. Hudec","is_ca":true},{"name":"Angel Y Wang","is_ca":true},{"name":"Melissa Vereschagin","is_ca":true},{"name":"Daniel Vigo","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.2664370795296838,"gpt":0.5197390405712066,"spread":0.2533019610415227,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002762955,0.0009978546,0.0004057735,0.001755633,0.0006816701,0.001585799,0.001410679,0.0008716073,0.005995503],"category_scores_gemma":[0.009219112,0.0004682082,0.001151377,0.0009176422,0.0005298003,0.002444544,0.003017629,0.001372616,0.002706503],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006500673,"about_ca_system_score_gemma":0.001147433,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003732204,"about_ca_topic_score_gemma":0.005729223,"domain_scores_codex":[0.9988878,0.0003440524,0.0001204803,0.0003254397,0.0002762682,0.00004588181],"domain_scores_gemma":[0.9956124,0.002723942,0.0003753424,0.0004992334,0.0004777009,0.0003114142],"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":[0.003084086,0.002369552,0.03035153,0.001688174,0.0009243026,0.003626606,0.009134012,0.03998194,0.08954437,0.01835923,0.08439159,0.7165446],"study_design_scores_gemma":[0.0003931335,0.0007836417,0.01043156,0.0001896973,0.000189295,0.0007688472,0.001173255,0.8501818,0.02946598,0.03139351,0.07477459,0.0002546441],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0749801,0.000203659,0.7775921,0.00178788,0.000238987,0.001873341,0.007964663,0.1322273,0.003132081],"genre_scores_gemma":[0.1731772,0.0001572435,0.8092398,0.0004971494,0.0001138862,0.001412143,0.007835566,0.00273958,0.004827447],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005995503,"threshold_uncertainty_score":0.02005696,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4396582907","doi":"10.1093/jamiaopen/ooae035","title":"Development of a chest X-ray machine learning convolutional neural network model on a budget and using artificial intelligence explainability techniques to analyze patterns of machine learning inference","year":2024,"lang":"en","type":"article","venue":"JAMIA Open","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Saskatchewan","funders":"University of Saskatchewan","keywords":"Inference; Artificial intelligence; Computer science; Machine learning; Convolutional neural network; Recall; Visualization; Artificial neural network; Contrast (vision); Precision and recall; Base (topology); Deep learning; Pattern recognition (psychology); Mathematics","authors":[{"name":"Stephen Lee","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.07760069511591254,"gpt":0.3773237843957666,"spread":0.2997230892798541,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005068303,0.0005182294,0.0003398844,0.0004313874,0.0002759102,0.0006684809,0.001249419,0.0008172153,0.003455789],"category_scores_gemma":[0.00160637,0.0004585491,0.0007153443,0.0002826219,0.000276445,0.0007612039,0.0004759625,0.001227551,0.0007084443],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001450879,"about_ca_system_score_gemma":0.001395021,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02835574,"about_ca_topic_score_gemma":0.02704433,"domain_scores_codex":[0.9998821,0.0000198898,0.000007660634,0.00003967421,0.00003266497,0.00001806881],"domain_scores_gemma":[0.9995158,0.0002120315,0.00004391131,0.00004063132,0.0001675523,0.00002011122],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006200498,0.00004764272,0.002424982,0.0000321367,0.00003697906,0.0001047558,0.00002996953,0.9576121,0.003496896,0.003051237,0.0008413795,0.0322599],"study_design_scores_gemma":[0.000001953948,0.000009349477,0.0001916045,0.000003105223,0.000004141283,0.000008508258,0.000002153528,0.9983892,0.0005932573,0.000612661,0.0001820797,0.000001849075],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1908332,0.0003005739,0.7965658,0.001272653,0.00009479508,0.0002399772,0.0007929514,0.002370043,0.007529921],"genre_scores_gemma":[0.8274866,0.0002099924,0.1624358,0.0001794737,0.00003243309,0.0003027116,0.0007838852,0.00013122,0.008437894],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02835574,"threshold_uncertainty_score":0.0563814,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4415507166","doi":"10.1093/jamiaopen/ooaf101","title":"Ethical sourcing in the context of health data supply chain management: a value sensitive design approach","year":2025,"lang":"en","type":"article","venue":"JAMIA Open","topic":"Ethics in Clinical Research","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Simon Fraser University","funders":"U.S. National Library of Medicine; National Institutes of Health","keywords":"Supply chain; Context (archaeology); Health data; Value (mathematics); Public health; Data collection; Supply chain management; Data integrity","authors":[{"name":"Camille Nebeker","is_ca":false},{"name":"Jean‐Christophe Bélisle‐Pipon","is_ca":true},{"name":"Benjamin Collins","is_ca":false},{"name":"Ashley Cordes","is_ca":false},{"name":"Kadija Ferryman","is_ca":false},{"name":"Brian McInnis","is_ca":false},{"name":"Shannon K. McWeeney","is_ca":false},{"name":"Laurie L. Novak","is_ca":false},{"name":"Susannah Rose","is_ca":false},{"name":"Joseph Yracheta","is_ca":false},{"name":"Ishan C. Williams","is_ca":false},{"name":"Xiaoqian Jiang","is_ca":false},{"name":"Ellen Wright Clayton","is_ca":false},{"name":"Bradley Malin","is_ca":false},{"name":"Nicholas G. Evans","is_ca":false},{"name":"Subhashini Chandrasekharan","is_ca":false},{"name":"Barbara J. Evans","is_ca":false},{"name":"Samantha Hurst","is_ca":false},{"name":"Aaron Lee","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.5629279325133483,"gpt":0.5845948011934361,"spread":0.02166686868008783,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.2291784,0.001515332,0.001058618,0.007351545,0.0104612,0.02868519,0.006330283,0.006684392,0.004630417],"category_scores_gemma":[0.1510237,0.002125302,0.002087704,0.004710777,0.04063656,0.01963982,0.02283337,0.008486082,0.0009392627],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02016378,"about_ca_system_score_gemma":0.04388119,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002424546,"about_ca_topic_score_gemma":0.003442668,"domain_scores_codex":[0.6374274,0.3294615,0.00708736,0.007075561,0.01568021,0.003268056],"domain_scores_gemma":[0.7017847,0.2289429,0.01361162,0.0267585,0.02294045,0.005961873],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001572353,0.0004793569,0.006035258,0.002156991,0.0001418126,0.0006619744,0.106415,0.007038692,0.002648382,0.7945308,0.003317944,0.07641656],"study_design_scores_gemma":[0.0002475191,0.0006441738,0.001593582,0.00522237,0.0001746334,0.0006542369,0.08624379,0.02277467,0.007066528,0.7204996,0.1547051,0.0001737256],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03999395,0.0008856137,0.8826761,0.02589125,0.0003033124,0.00507659,0.0001603006,0.0002898683,0.044723],"genre_scores_gemma":[0.2859395,0.0007902191,0.7019045,0.002741779,0.00008711847,0.005182952,0.0001448584,0.0001633928,0.003045646],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.2291784,"threshold_uncertainty_score":0.9505603,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4376642717","doi":"10.1093/jamiaopen/ooad032","title":"A metadata framework for computational phenotypes","year":2023,"lang":"en","type":"article","venue":"JAMIA Open","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Calgary","funders":"National Institute of General Medical Sciences; National Center for Advancing Translational Sciences; National Human Genome Research Institute; Cincinnati Children's Hospital Medical Center","keywords":"Metadata; Computer science; Phenotype; Information retrieval; Computational biology; World Wide Web; Biology; Genetics","authors":[{"name":"Henry M. Spotnitz","is_ca":false},{"name":"Nripendra Acharya","is_ca":false},{"name":"James J. Cimino","is_ca":false},{"name":"Shawn N. Murphy","is_ca":false},{"name":"Bahram Namjou","is_ca":false},{"name":"Nancy A. Crimmins","is_ca":false},{"name":"Theresa L. Walunas","is_ca":false},{"name":"Cong Liu","is_ca":false},{"name":"David R. Crosslin","is_ca":false},{"name":"Barbara Benoit","is_ca":false},{"name":"Elisabeth A. Rosenthal","is_ca":false},{"name":"Jennifer A. Pacheco","is_ca":false},{"name":"Anna Ostropolets","is_ca":false},{"name":"Harry Reyes Nieva","is_ca":false},{"name":"Jason Patterson","is_ca":false},{"name":"Lauren R. Richter","is_ca":false},{"name":"Tiffany J. Callahan","is_ca":false},{"name":"Ahmed El‐Hussein","is_ca":false},{"name":"Chao Pang","is_ca":false},{"name":"Krzysztof Kiryluk","is_ca":false},{"name":"Jordan G. Nestor","is_ca":false},{"name":"Atlas Khan","is_ca":false},{"name":"Sumit Mohan","is_ca":false},{"name":"Evan Minty","is_ca":true},{"name":"Wendy K. Chung","is_ca":false},{"name":"Wei‐Qi Wei","is_ca":false},{"name":"Karthik Natarajan","is_ca":false},{"name":"Chunhua Weng","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.06756581596636699,"gpt":0.3844595889207631,"spread":0.3168937729543961,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.04911267,0.001023486,0.0009606077,0.01328825,0.00372622,0.008420734,0.003591855,0.001795699,0.003219912],"category_scores_gemma":[0.08937038,0.0008716006,0.002102912,0.009345523,0.004286005,0.02021857,0.008251883,0.002529082,0.001069867],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004296074,"about_ca_system_score_gemma":0.008807824,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0100146,"about_ca_topic_score_gemma":0.01303169,"domain_scores_codex":[0.9742656,0.01426175,0.004908606,0.002369625,0.003737554,0.0004569193],"domain_scores_gemma":[0.9050062,0.05527462,0.008080177,0.0138724,0.01563055,0.00213611],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000391474,0.0005506673,0.01919254,0.001629824,0.0001499065,0.0004930379,0.02674696,0.008832496,0.00640014,0.5846563,0.01298979,0.3379667],"study_design_scores_gemma":[0.0001749811,0.0004546939,0.01130217,0.002817502,0.0003038711,0.001094811,0.0236139,0.07600491,0.008638986,0.5949529,0.2802647,0.0003767051],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01494923,0.0004020561,0.9674097,0.003629085,0.0001170811,0.001353376,0.002668715,0.002685447,0.006785299],"genre_scores_gemma":[0.0667296,0.0002125222,0.9263961,0.0003690982,0.0000494262,0.001075007,0.003995781,0.000270591,0.0009019093],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.04911267,"threshold_uncertainty_score":0.2597357,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4383618376","doi":"10.1093/jamiaopen/ooad046","title":"AnnoDash, a clinical terminology annotation dashboard","year":2023,"lang":"en","type":"article","venue":"JAMIA Open","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Institute for Clinical Evaluative Sciences; SickKids Foundation; Hospital for Sick Children","funders":"","keywords":"Computer science; SNOMED CT; Information retrieval; Terminology; Ontology; Annotation; Dashboard; Ranking (information retrieval); Interoperability; Interface (matter); Data science; World Wide Web; Artificial intelligence","authors":[{"name":"Justin Xu","is_ca":true},{"name":"Mjaye Mazwi","is_ca":true},{"name":"Alistair E. W. Johnson","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.09907901780984156,"gpt":0.435239821340387,"spread":0.3361608035305454,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008827553,0.002771909,0.001367795,0.00520833,0.001039726,0.005372138,0.003490587,0.001786703,0.06039182],"category_scores_gemma":[0.03969884,0.001151791,0.001282871,0.00389639,0.0008066127,0.006334949,0.007885338,0.00247192,0.02614248],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001617914,"about_ca_system_score_gemma":0.002561329,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003931088,"about_ca_topic_score_gemma":0.004572073,"domain_scores_codex":[0.9942978,0.001136826,0.0008937216,0.001076778,0.002360443,0.0002344496],"domain_scores_gemma":[0.9696144,0.0147668,0.00234141,0.00582096,0.005379548,0.002076898],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001818098,0.0003076224,0.004729501,0.001508903,0.0001437523,0.0009231221,0.00124728,0.002402413,0.005256208,0.007316286,0.6532911,0.3210557],"study_design_scores_gemma":[0.0004045019,0.0001934526,0.005401256,0.0006182418,0.0000796552,0.000558254,0.0004465064,0.01739445,0.01128562,0.01356381,0.9498198,0.0002345499],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"software","genre_gemma":"methods","genre_scores_codex":[0.01278654,0.001265451,0.2111298,0.005131392,0.002413173,0.001644638,0.1014098,0.6345719,0.02964739],"genre_scores_gemma":[0.07433262,0.002143663,0.5313172,0.005561588,0.001132068,0.00371335,0.2550169,0.07056973,0.05621289],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.06039182,"threshold_uncertainty_score":0.2020307,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4406091310","doi":"10.1093/jamiaopen/ooae158","title":"Multi-modal prediction of extracorporeal support—a resource intensive therapy, utilizing a large national database","year":2024,"lang":"en","type":"article","venue":"JAMIA Open","topic":"Mechanical Circulatory Support Devices","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"National Center for Advancing Translational Sciences; National Institute on Drug Abuse; Washington University in St. Louis; National Institutes of Health; National Heart, Lung, and Blood Institute; St. Louis Children's Hospital; Children's Discovery Institute","keywords":"Triage; Extracorporeal membrane oxygenation; Computer science; Intensive care; Machine learning; Artificial intelligence; Medicine; Intensive care medicine; Emergency medicine","authors":[{"name":"Bing Xue","is_ca":false},{"name":"Neel Shah","is_ca":true},{"name":"Philip Payne","is_ca":false},{"name":"Ahmed S. Said","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.07110794668121544,"gpt":0.3094853716080438,"spread":0.2383774249268283,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002708805,0.0004850072,0.0004673385,0.001017045,0.0001909881,0.0008516317,0.0005917337,0.000524147,0.0006748893],"category_scores_gemma":[0.006058766,0.0001664435,0.0005425393,0.0009047307,0.0001512702,0.0005577982,0.000750127,0.0008549959,0.0003037236],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007919574,"about_ca_system_score_gemma":0.001025561,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01755702,"about_ca_topic_score_gemma":0.02093877,"domain_scores_codex":[0.9992957,0.0001898736,0.00007499017,0.0002666018,0.0001101748,0.00006251696],"domain_scores_gemma":[0.9971661,0.001256798,0.0005812112,0.0003620531,0.0004214626,0.0002123559],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005806223,0.0003708152,0.8291733,0.00008186771,0.0003261118,0.0002572325,0.00008349937,0.1128518,0.00114948,0.0004528462,0.006152042,0.04852038],"study_design_scores_gemma":[0.00004146252,0.0002313951,0.2165168,0.00005581298,0.00008502643,0.0001611743,0.00013316,0.7789365,0.001116675,0.0009136765,0.001779007,0.00002935124],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9669856,0.0003881877,0.01314718,0.001069814,0.00005819327,0.0000917232,0.0170425,0.0002075421,0.001009261],"genre_scores_gemma":[0.975526,0.0001327403,0.008125708,0.0001062747,0.0000387639,0.00004936977,0.01575818,0.000009213699,0.0002537293],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01755702,"threshold_uncertainty_score":0.03490967,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4417065257","doi":"10.1093/jamiaopen/ooaf171","title":"Evaluation and improvement of algorithmic fairness for COVID-19 severity classification using Explainable Artificial Intelligence-based bias mitigation","year":2025,"lang":"en","type":"article","venue":"JAMIA Open","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"University of British Columbia, Okanagan Campus; University of British Columbia; University of Toronto; Mila - Quebec Artificial Intelligence Institute; University Health Network; McGill University; Jewish General Hospital; Toronto Rehabilitation Institute; McGill University Health Centre","funders":"","keywords":"Risk assessment; Risk stratification; Decision support system; Intervention (counseling); Resource (disambiguation); Risk management","authors":[{"name":"Shayan Nejadshamsi","is_ca":true},{"name":"Charlene H. Chu","is_ca":true},{"name":"Katherine S. McGilton","is_ca":true},{"name":"Xiaoxiao Li","is_ca":true},{"name":"Charlene Ronquillo","is_ca":true},{"name":"Samira Abbasgholizadeh Rahimi","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.5020705498682053,"gpt":0.5350747081248598,"spread":0.03300415825665448,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01745318,0.001091125,0.001114831,0.001109551,0.0008179843,0.001671877,0.002070429,0.001380723,0.001325577],"category_scores_gemma":[0.04013894,0.0003002778,0.0007648876,0.0004963559,0.001259682,0.0018816,0.00221499,0.002110387,0.0001835644],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002163254,"about_ca_system_score_gemma":0.003206352,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003577154,"about_ca_topic_score_gemma":0.00309401,"domain_scores_codex":[0.9947276,0.003095579,0.0002570345,0.0007249758,0.0008465183,0.0003482342],"domain_scores_gemma":[0.9736751,0.0192759,0.001681068,0.002183721,0.002426719,0.0007575864],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001008127,0.0005043366,0.03520716,0.00020597,0.000253615,0.0001395377,0.0003754,0.7622214,0.00258984,0.01577463,0.002260544,0.1794594],"study_design_scores_gemma":[0.00003407733,0.000156614,0.001057225,0.00001870856,0.00002184221,0.00001834672,0.00003982357,0.9913198,0.001219454,0.005848354,0.0002565827,0.000009092935],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3875518,0.001002237,0.6040169,0.001818854,0.0002279166,0.0005551697,0.0002464831,0.0009776038,0.003602943],"genre_scores_gemma":[0.9194345,0.0001022897,0.07909627,0.0002666461,0.00006657601,0.0001308815,0.0002036173,0.00003456234,0.0006647687],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01745318,"threshold_uncertainty_score":0.09230232,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4416046673","doi":"10.1093/jamiaopen/ooaf143","title":"Patient and clinician perspectives in the use of machine learning and artificial intelligence in the context of acute neurology","year":2025,"lang":"en","type":"article","venue":"JAMIA Open","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Kellogg's (Canada)","funders":"National Institutes of Health","keywords":"Context (archaeology); Work (physics); Clinical decision making; Neurology; MEDLINE","authors":[{"name":"Egide Abahuje","is_ca":false},{"name":"Ethan J. Houskamp","is_ca":false},{"name":"Juliana Silva Pinheiro do Nascimento","is_ca":false},{"name":"Elaf Agha","is_ca":false},{"name":"William K. Thompson","is_ca":true},{"name":"Kelly N. Michelson","is_ca":false},{"name":"Andrew M. Naidech","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.2148693527482158,"gpt":0.4641221921554229,"spread":0.2492528394072072,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01511319,0.0002384503,0.0003651726,0.0009814636,0.001715725,0.003070391,0.0004686722,0.0009956245,0.001509762],"category_scores_gemma":[0.04474609,0.0002417483,0.0004464494,0.0006199161,0.00264696,0.002049976,0.00244735,0.001873343,0.0001748767],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002058364,"about_ca_system_score_gemma":0.001840195,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001778669,"about_ca_topic_score_gemma":0.002688049,"domain_scores_codex":[0.9830215,0.01327766,0.0008992447,0.0003811028,0.001609586,0.0008109756],"domain_scores_gemma":[0.9552587,0.02979253,0.0077487,0.0003920016,0.003980542,0.002827553],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0003954828,0.0001208238,0.1991952,0.0008279109,0.0001093804,0.001738766,0.7566115,0.0002941785,0.002838644,0.001666465,0.003385118,0.03281654],"study_design_scores_gemma":[0.00002313086,0.0004082209,0.08394648,0.000781122,0.00005731771,0.00226213,0.8967578,0.0007312711,0.001195152,0.001243109,0.0125112,0.00008316907],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9886211,0.0008510063,0.0007474015,0.005589031,0.0000681427,0.00003290261,0.00009343806,0.000007008122,0.003989979],"genre_scores_gemma":[0.9977626,0.0005936999,0.0003993269,0.0009248272,0.00004210581,0.000026117,0.00003060985,0.000004432332,0.0002162632],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01511319,"threshold_uncertainty_score":0.07992715,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4406694526","doi":"10.1093/jamiaopen/ooae152","title":"pyDeid: an improved, fast, flexible, and generalizable rule-based approach for deidentification of free-text medical records","year":2024,"lang":"en","type":"article","venue":"JAMIA Open","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true},"ca_institutions":"University of Toronto; Hospital for Sick Children; St. Michael's Hospital","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Canadian Frailty Network; Canadian Cancer Society","keywords":"Computer science; Python (programming language); Software; Precision and recall; Identification (biology); Benchmark (surveying); Data mining; Artificial intelligence; Extant taxon; Flexibility (engineering); Machine learning; Recall; Information retrieval; Natural language processing; Programming language","authors":[{"name":"Vaakesan Sundrelingam","is_ca":true},{"name":"Shireen Parimoo","is_ca":true},{"name":"Frances Pogacar","is_ca":false},{"name":"Radha Koppula","is_ca":true},{"name":"Saeha Shin","is_ca":true},{"name":"Chloé Pou-Prom","is_ca":false},{"name":"Surain B. Roberts","is_ca":true},{"name":"Amol A. Verma","is_ca":true},{"name":"Fahad Razak","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03624260455257254,"gpt":0.3462986527902708,"spread":0.3100560482376983,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007651795,0.001682661,0.001460371,0.005303482,0.0009901244,0.003953929,0.004954693,0.001291187,0.005721098],"category_scores_gemma":[0.03183748,0.001095087,0.0020854,0.003189991,0.001040951,0.004078426,0.005909091,0.002957626,0.005748603],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001273091,"about_ca_system_score_gemma":0.005560177,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006617357,"about_ca_topic_score_gemma":0.007341954,"domain_scores_codex":[0.9911649,0.001205914,0.001688199,0.002282124,0.003367348,0.0002915301],"domain_scores_gemma":[0.9864669,0.006346565,0.001491744,0.00287691,0.002330129,0.0004876865],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001154658,0.0005759577,0.02532645,0.002732219,0.0006706291,0.001550558,0.001077065,0.02077716,0.01681793,0.01288459,0.199582,0.7168509],"study_design_scores_gemma":[0.0006567708,0.0003764525,0.01710661,0.0008988712,0.0002611674,0.004362083,0.0006577267,0.4882409,0.09108159,0.0499218,0.3458259,0.0006101639],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01338821,0.001034361,0.7202505,0.001175792,0.0004170476,0.001170253,0.02952912,0.229138,0.0038968],"genre_scores_gemma":[0.05705756,0.0007551227,0.8717951,0.001505664,0.0001180358,0.000862275,0.05706061,0.005064494,0.005781098],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007651795,"threshold_uncertainty_score":0.04046702,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4414889376","doi":"10.1093/jamiaopen/ooaf111","title":"Opportunities, barriers, and remedies for implementing REDCap integration with electronic health records via Fast Healthcare Interoperability Resources (FHIR)","year":2025,"lang":"en","type":"article","venue":"JAMIA Open","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"U.S. National Library of Medicine; Seattle Children's Research Institute; University of Texas Health Science Center at San Antonio; Marshfield Clinic Research Institute; University of Texas Health Science Center at Houston; Children’s Hospital of Wisconsin Research Institute; Women's College Hospital; Nova Southeastern University; Johns Hopkins University; National Center for Advancing Translational Sciences; Children's Hospital Colorado; Center for Clinical and Translational Science, University of Kentucky; Yale University","keywords":"Interoperability; Health records; Health care; System integration; Quality (philosophy); Healthcare system; Health data; Meaningful use","authors":[{"name":"Alex Cheng","is_ca":false},{"name":"Cathy Shyr","is_ca":false},{"name":"Adam Lewis","is_ca":false},{"name":"Francesco Delacqua","is_ca":false},{"name":"Teresa Bosler","is_ca":false},{"name":"Mary K. Banasiewicz","is_ca":false},{"name":"Robert J. Taylor","is_ca":false},{"name":"Christopher J. Lindsell","is_ca":false},{"name":"Paul A. Harris","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.0898978734849532,"gpt":0.4420570598260447,"spread":0.3521591863410915,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.05907919,0.0006042519,0.0003590531,0.001622889,0.004371324,0.0101631,0.002393311,0.002952502,0.007599771],"category_scores_gemma":[0.1369372,0.0006751627,0.0009622148,0.001560697,0.003603778,0.01072611,0.007711379,0.004930164,0.0009032522],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004693244,"about_ca_system_score_gemma":0.02565725,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008369595,"about_ca_topic_score_gemma":0.01128018,"domain_scores_codex":[0.9308634,0.03607982,0.006596807,0.002682999,0.01276056,0.01101639],"domain_scores_gemma":[0.8229641,0.1079608,0.03185374,0.008984863,0.0164519,0.01178461],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"qualitative","study_design_scores_codex":[0.0003787861,0.003398231,0.4208736,0.003165896,0.0001746486,0.003080266,0.06963957,0.001628242,0.006176639,0.05755163,0.0288329,0.4050996],"study_design_scores_gemma":[0.0002080145,0.002243852,0.4007481,0.01390488,0.0003757468,0.003709206,0.3666969,0.009853143,0.01245342,0.0318943,0.1573761,0.000536358],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6813496,0.002450389,0.02530062,0.2447188,0.0004988091,0.001327689,0.0002450953,0.001058038,0.04305086],"genre_scores_gemma":[0.9673778,0.001009574,0.01938052,0.008368185,0.0001292477,0.0005513674,0.0001212107,0.00007081996,0.00299125],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05907919,"threshold_uncertainty_score":0.3124443,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4416935767","doi":"10.1093/jamiaopen/ooaf158","title":"Evaluating sociodemographic bias in a deployed machine-learned patient deterioration model","year":2025,"lang":"en","type":"article","venue":"JAMIA Open","topic":"Homelessness and Social Issues","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Public Health Ontario; University of Toronto; St. Michael's Hospital","funders":"","keywords":"Standardization; Risk assessment; Decision support system; MEDLINE; Data collection","authors":[{"name":"Michael Colacci","is_ca":true},{"name":"Chloé Pou-Prom","is_ca":true},{"name":"Arjumand Siddiqi","is_ca":true},{"name":"Muhammad Mamdani","is_ca":true},{"name":"Amol A. Verma","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.288285744714407,"gpt":0.5431989938870504,"spread":0.2549132491726434,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.03728166,0.0007822284,0.0008473348,0.0009534282,0.0004125157,0.001299601,0.001091519,0.0008217045,0.001139274],"category_scores_gemma":[0.07228839,0.0003769784,0.00114064,0.0004873033,0.0008712793,0.0009419198,0.001350795,0.001307537,0.0001787363],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001669681,"about_ca_system_score_gemma":0.001685648,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008415349,"about_ca_topic_score_gemma":0.003667073,"domain_scores_codex":[0.9919751,0.005602748,0.0005291902,0.001034816,0.0005556147,0.00030239],"domain_scores_gemma":[0.9332902,0.05462289,0.005100803,0.002836694,0.003399799,0.0007495682],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001529167,0.0002969637,0.5762857,0.0001009331,0.0008611868,0.0001210866,0.0001765414,0.3902938,0.000431486,0.001307853,0.0009581106,0.02763704],"study_design_scores_gemma":[0.00008138957,0.0005335025,0.02676389,0.00005287829,0.0001326104,0.00004975852,0.0000716382,0.969326,0.0008394818,0.001837806,0.0002921179,0.00001901109],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9640022,0.0002931234,0.03351358,0.0008208615,0.00006149487,0.0001374987,0.0003592214,0.0001612819,0.0006508323],"genre_scores_gemma":[0.9951321,0.00003303407,0.004303464,0.00009880688,0.00001963613,0.00003190591,0.0002683775,0.00000628508,0.0001063402],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9627184,"threshold_uncertainty_score":0.1971666,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4408177747","doi":"10.1093/jamiaopen/ooaf010","title":"Semantic enrichment of Pomeranian health study data using LOINC and WHO-FIC terminology mapping principles","year":2025,"lang":"en","type":"article","venue":"JAMIA Open","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Victoria","funders":"","keywords":"Terminology; Computer science; Information retrieval; Natural language processing; Linguistics; Philosophy","authors":[{"name":"Esther Thea Inau","is_ca":false},{"name":"Dörte Radke","is_ca":false},{"name":"Linda Bird","is_ca":true},{"name":"Susanne Westphal","is_ca":false},{"name":"Till Ittermann","is_ca":false},{"name":"Christian Schäfer","is_ca":false},{"name":"Matthias Nauck","is_ca":false},{"name":"Atinkut Alamirrew Zeleke","is_ca":false},{"name":"Carsten Oliver Schmidt","is_ca":false},{"name":"Dagmar Waltemath","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1301853124132846,"gpt":0.3993251602189576,"spread":0.269139847805673,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02785616,0.001002844,0.0008983005,0.0166048,0.001895176,0.005005967,0.001988045,0.001038993,0.00505162],"category_scores_gemma":[0.07494619,0.0007153258,0.00175212,0.01148138,0.00256346,0.006356058,0.008512426,0.001960001,0.001816366],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003573245,"about_ca_system_score_gemma":0.01051482,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007844621,"about_ca_topic_score_gemma":0.007461431,"domain_scores_codex":[0.9830478,0.008072326,0.004110491,0.002194581,0.002203628,0.0003711629],"domain_scores_gemma":[0.9433311,0.03160315,0.004641106,0.01237185,0.007059131,0.0009935488],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001241201,0.0003219784,0.05294768,0.01185377,0.0004689255,0.00243129,0.04696563,0.007100915,0.01778424,0.2466158,0.09532842,0.5169402],"study_design_scores_gemma":[0.0001383111,0.0001401127,0.02464991,0.004941603,0.0003568221,0.001281305,0.01052571,0.01234759,0.01680684,0.1066563,0.8219325,0.0002229397],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.06338824,0.001919945,0.8135523,0.008049939,0.0009107646,0.003803541,0.06586702,0.007289863,0.03521843],"genre_scores_gemma":[0.09610923,0.0009601522,0.8459166,0.001279769,0.0001721514,0.0026034,0.0494535,0.001199105,0.002306152],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02785616,"threshold_uncertainty_score":0.1473192,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4416935774","doi":"10.1093/jamiaopen/ooaf134","title":"Biomedical data repositories require governance for artificial intelligence/machine learning applications at every step","year":2025,"lang":"en","type":"article","venue":"JAMIA Open","topic":"Scientific Computing and Data Management","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Simon Fraser University","funders":"National Human Genome Research Institute; National Institutes of Health","keywords":"Corporate governance; Data collection; Data governance; Information governance; Clinical governance","authors":[{"name":"Ellen Wright Clayton","is_ca":false},{"name":"Susannah Rose","is_ca":false},{"name":"Camille Nebecker","is_ca":false},{"name":"Laurie L. Novak","is_ca":false},{"name":"Yaël Bensoussan","is_ca":false},{"name":"You Chen","is_ca":false},{"name":"Benjamin Collins","is_ca":false},{"name":"Ashley Cordes","is_ca":false},{"name":"Barbara J. Evans","is_ca":false},{"name":"Kadija Ferryman","is_ca":false},{"name":"Samantha Hurst","is_ca":false},{"name":"Xiaoqian Jiang","is_ca":false},{"name":"Aaron Lee","is_ca":false},{"name":"Shannon K. McWeeney","is_ca":false},{"name":"Jillian A. Parker","is_ca":false},{"name":"Jean‐Christophe Bélisle‐Pipon","is_ca":true},{"name":"Eric S. Rosenthal","is_ca":false},{"name":"Zhijun Yin","is_ca":false},{"name":"Joseph Yracheta","is_ca":false},{"name":"Bradley Malin","is_ca":false},{"name":"Nicholas G. Evans","is_ca":false},{"name":"Subhashini Chandrasekharan","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.2400211051165123,"gpt":0.4668468828146544,"spread":0.2268257776981421,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch","open_science"],"consensus_categories":[],"category_scores_codex":[0.3941848,0.0008883152,0.001578821,0.003683493,0.009030686,0.02985091,0.008526342,0.008622548,0.007228841],"category_scores_gemma":[0.397418,0.001936594,0.001533677,0.005160299,0.02290495,0.03923187,0.02929673,0.02035463,0.005559275],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01034345,"about_ca_system_score_gemma":0.08283409,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006197156,"about_ca_topic_score_gemma":0.006156396,"domain_scores_codex":[0.6075388,0.2796352,0.03275317,0.02001891,0.05124349,0.008810478],"domain_scores_gemma":[0.3164233,0.2482353,0.03509976,0.2619028,0.1142526,0.02408616],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002612997,0.000537773,0.01727244,0.001380668,0.0002167469,0.0005065781,0.02095288,0.002411357,0.002904002,0.5946016,0.1677101,0.1912445],"study_design_scores_gemma":[0.0001542699,0.0002008871,0.006098225,0.003750767,0.00007979578,0.0005968332,0.01179518,0.003774004,0.002930885,0.3733402,0.5970141,0.0002647929],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.02047199,0.00292502,0.3691967,0.5390124,0.003201972,0.006403311,0.001489248,0.002428134,0.05487131],"genre_scores_gemma":[0.2638858,0.003530276,0.5475815,0.1394465,0.004220874,0.0134042,0.004399239,0.002119485,0.02141208],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.9914737,"threshold_uncertainty_score":0.7470781,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W7124425818","doi":"10.1093/jamiaopen/ooaf179","title":"MedSlice: fine-tuned large language models for secure clinical note sectioning","year":2025,"lang":"en","type":"article","venue":"JAMIA Open","topic":"Topic Modeling","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McGill University; McGill University Health Centre","funders":"","keywords":"Language model; Key (lock); Modeling language; Natural language; Action (physics)","authors":[{"name":"Joshua Davis","is_ca":false},{"name":"Thomas Sounack","is_ca":false},{"name":"Kate Sciacca","is_ca":false},{"name":"Jessie M Brain","is_ca":false},{"name":"Brigitte N. Durieux","is_ca":true},{"name":"Nicole Agaronnik","is_ca":false},{"name":"Charlotta Lindvall","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04370099868506119,"gpt":0.3979130537276389,"spread":0.3542120550425777,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004238366,0.001539958,0.0006466681,0.001755747,0.0005149377,0.001815351,0.002238318,0.001465298,0.006657288],"category_scores_gemma":[0.0203186,0.0007445854,0.002053326,0.000830297,0.0004737263,0.002171463,0.002419803,0.002424008,0.005125589],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001609781,"about_ca_system_score_gemma":0.003221545,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01437942,"about_ca_topic_score_gemma":0.02332769,"domain_scores_codex":[0.9981726,0.0006908724,0.000221697,0.0005634978,0.0002495896,0.0001015973],"domain_scores_gemma":[0.9924181,0.005412971,0.0003972205,0.0008958227,0.000646379,0.0002294682],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002529393,0.0006377128,0.02303517,0.001462147,0.0009257299,0.001071781,0.001158902,0.1736427,0.01444068,0.00669713,0.1409898,0.6334089],"study_design_scores_gemma":[0.0003621585,0.000224474,0.003359691,0.0002015693,0.0001759125,0.0004404017,0.0002339359,0.9330569,0.0130962,0.01442321,0.03431014,0.0001154624],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06063755,0.002854551,0.6703302,0.002099008,0.0006305999,0.001087415,0.0263789,0.232283,0.00369883],"genre_scores_gemma":[0.3390689,0.001108417,0.5982552,0.001345101,0.0002357754,0.00143085,0.04808149,0.005386527,0.005087731],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01437942,"threshold_uncertainty_score":0.02859145,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4410090741","doi":"10.1093/jamiaopen/ooaf030","title":"Evaluation of a score for identifying hospital stays that trigger a pharmacist intervention: integration into a clinical decision support system","year":2025,"lang":"en","type":"article","venue":"JAMIA Open","topic":"Pharmaceutical Practices and Patient Outcomes","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Medicine; Pharmacist; Medical prescription; Observational study; Pharmacy; Clinical decision support system; Clinical pharmacy; Intervention (counseling); Emergency medicine; Retrospective cohort study; Medical emergency; Family medicine; Decision support system; Internal medicine; Nursing; Data mining","authors":[{"name":"Laurine Robert","is_ca":false},{"name":"Nathalie Vidoni","is_ca":false},{"name":"Erwin Gerard","is_ca":false},{"name":"Emmanuel Chazard","is_ca":false},{"name":"Pascal Odou","is_ca":false},{"name":"Chloé Rousselière","is_ca":false},{"name":"Bertrand Décaudin","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.4784415037097957,"gpt":0.5959051680463093,"spread":0.1174636643365136,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008663392,0.001002193,0.001721802,0.004451291,0.0004899091,0.002466627,0.0008278259,0.0007517558,0.001523025],"category_scores_gemma":[0.03015523,0.0003051516,0.001475039,0.002667886,0.0003322496,0.00124612,0.00115479,0.0006934101,0.0004058679],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001445273,"about_ca_system_score_gemma":0.002585583,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004104423,"about_ca_topic_score_gemma":0.004744939,"domain_scores_codex":[0.9922991,0.002616027,0.001503654,0.0005562432,0.00263894,0.0003860421],"domain_scores_gemma":[0.979908,0.010177,0.003448586,0.0004322179,0.004558442,0.001475738],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001883666,0.0005981129,0.9071046,0.0003445229,0.000519778,0.0001508329,0.0002392921,0.004458451,0.001107074,0.0003332889,0.002216168,0.0810442],"study_design_scores_gemma":[0.0005673204,0.004711935,0.8155494,0.000336829,0.001004734,0.0009617205,0.0008688222,0.1673734,0.004621456,0.001085048,0.002768564,0.0001508707],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9600223,0.000679567,0.02999038,0.0008123569,0.0001094017,0.001321923,0.002101503,0.0007089147,0.004253512],"genre_scores_gemma":[0.9537868,0.0001682359,0.04404164,0.00009857725,0.00005094931,0.0003728427,0.001195028,0.00001861061,0.0002674688],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008663392,"threshold_uncertainty_score":0.0458169,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4415355996","doi":"10.1093/jamiaopen/ooaf118","title":"Development and evaluation of a patient-centric approach for accurate medication capture","year":2025,"lang":"en","type":"article","venue":"JAMIA Open","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University College of the North","funders":"Sutter Health","keywords":"Health care; Digital health; Data collection; Process (computing); Health data","authors":[{"name":"Larry Ma","is_ca":true},{"name":"Joshua Ide","is_ca":false},{"name":"Rachel Weinstein","is_ca":false},{"name":"Sebastien Hannay","is_ca":false},{"name":"Lucie Keunen","is_ca":false},{"name":"Vincent Keunen","is_ca":false},{"name":"И. С. Попова","is_ca":false},{"name":"Sherry Yan","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1258992520330229,"gpt":0.483911295560625,"spread":0.3580120435276022,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02422299,0.001022319,0.0005811141,0.000982438,0.0003812038,0.002185486,0.002152353,0.0013484,0.001409852],"category_scores_gemma":[0.0357025,0.000503469,0.0007847452,0.000454479,0.0005625085,0.001583639,0.002260924,0.001060866,0.0007122651],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009789421,"about_ca_system_score_gemma":0.003619117,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001044286,"about_ca_topic_score_gemma":0.001636368,"domain_scores_codex":[0.9760196,0.0129118,0.002313944,0.001820456,0.00638188,0.0005523385],"domain_scores_gemma":[0.9654548,0.01476346,0.00316547,0.003709866,0.01138283,0.001523535],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.003056448,0.007146608,0.1294804,0.002697947,0.000637212,0.000928698,0.005809846,0.007606454,0.06386141,0.001707167,0.008831297,0.7682365],"study_design_scores_gemma":[0.002938529,0.05213784,0.4084595,0.002757986,0.001871302,0.008547873,0.005214721,0.1843779,0.2436626,0.002991728,0.0862938,0.0007462],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5896613,0.0007320101,0.3758837,0.001864708,0.0002444101,0.01539667,0.001760421,0.008726746,0.005730023],"genre_scores_gemma":[0.3437622,0.0002743799,0.647794,0.001111752,0.00007907546,0.003909897,0.001375134,0.0002116218,0.001481857],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02422299,"threshold_uncertainty_score":0.1281049,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4412816915","doi":"10.1093/jamiaopen/ooaf085","title":"Assessment of 3 standards-based clinical decision support (CDS) tools in an academic electronic health record using Clinical Quality Language, CDS Hooks, and Fast Healthcare Interoperability Resources: a retrospective evaluation","year":2025,"lang":"en","type":"article","venue":"JAMIA Open","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Covenant Health","funders":"Agency for Healthcare Research and Quality","keywords":"SNOMED CT; Interoperability; Clinical decision support system; Medicine; Health care; Medical emergency; Mammography; Medical physics; Family medicine; Decision support system; Artificial intelligence; Breast cancer; Computer science; Cancer; Terminology; World Wide Web","authors":[{"name":"Mark Isabelle","is_ca":false},{"name":"Ivan K. Ip","is_ca":true},{"name":"Louise Schneider","is_ca":false},{"name":"Ali S. Raja","is_ca":false},{"name":"Sayon Dutta","is_ca":false},{"name":"Adam Landman","is_ca":false},{"name":"Ronilda Lacson","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.3047308766552961,"gpt":0.6814308393292652,"spread":0.3766999626739691,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02924315,0.0004942512,0.0009781343,0.005925657,0.0007697215,0.00210385,0.0008793352,0.0007875165,0.0008618208],"category_scores_gemma":[0.08233717,0.0005785746,0.001451689,0.005799631,0.001359106,0.002118913,0.001919481,0.0006653139,0.0002703696],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002573646,"about_ca_system_score_gemma":0.002448293,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004291493,"about_ca_topic_score_gemma":0.00354584,"domain_scores_codex":[0.9587117,0.01624963,0.01206082,0.003160241,0.008664609,0.001152943],"domain_scores_gemma":[0.8578666,0.05394159,0.04888239,0.007444038,0.02901144,0.002854004],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003455869,0.0001235107,0.9955097,0.0001039017,0.0001080348,0.00003981535,0.0004878509,0.00009352535,0.00006039269,0.00004727888,0.00006442294,0.003015949],"study_design_scores_gemma":[0.0001512805,0.002565745,0.9866497,0.000217168,0.0004428917,0.0005186597,0.004271439,0.002649488,0.001232254,0.0001123918,0.001138322,0.00005084002],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9963703,0.000454553,0.001058859,0.00005071635,0.000008438742,0.000600435,0.0009272292,0.00001366854,0.0005158035],"genre_scores_gemma":[0.9965006,0.0001235634,0.001942345,0.00004985346,0.00001019767,0.000432386,0.0008698406,0.000005734299,0.0000654708],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02924315,"threshold_uncertainty_score":0.1546544,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4415854845","doi":"10.1093/jamiaopen/ooaf141","title":"Assessing the acceptability and usability of MedSafer, a patient-centered electronic deprescribing tool","year":2025,"lang":"en","type":"article","venue":"JAMIA Open","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Jewish General Hospital; McGill University; McGill University Health Centre","funders":"Health Canada","keywords":"Deprescribing; Usability; Electronic prescribing; Medication adherence; Data collection; Beers Criteria","authors":[{"name":"Jimin J. Lee","is_ca":true},{"name":"Eva Filosa","is_ca":true},{"name":"Tiphaine Pierson","is_ca":false},{"name":"Ninh Khuong","is_ca":false},{"name":"Camille Gagnon","is_ca":false},{"name":"Jennie Herbin","is_ca":false},{"name":"Soham Rej","is_ca":true},{"name":"Claire Godard‐Sebillotte","is_ca":true},{"name":"Robyn Tamblyn","is_ca":true},{"name":"Todd C. Lee","is_ca":true},{"name":"Emily G. McDonald","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.07412632237279924,"gpt":0.471417267383996,"spread":0.3972909450111968,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0152676,0.000415235,0.0003698891,0.0006863379,0.0003478381,0.0009175491,0.000408142,0.0005556041,0.001037567],"category_scores_gemma":[0.03330322,0.0002916171,0.0008763691,0.0003022657,0.0004203786,0.0009000332,0.000997953,0.0004483055,0.0001601297],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000438131,"about_ca_system_score_gemma":0.00063188,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008119046,"about_ca_topic_score_gemma":0.00104496,"domain_scores_codex":[0.990765,0.005591587,0.001084456,0.0004003628,0.001807706,0.0003509921],"domain_scores_gemma":[0.9746848,0.01823306,0.002708204,0.0006102373,0.003126395,0.000637418],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003250547,0.004696892,0.7781222,0.00177565,0.0004012097,0.0005302512,0.0349634,0.0007054942,0.009492951,0.0001862153,0.001228416,0.1646467],"study_design_scores_gemma":[0.0003410338,0.02620208,0.9392735,0.000338223,0.00033599,0.000960358,0.01984488,0.004704386,0.005006282,0.0001314583,0.002737605,0.0001243376],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9988143,0.00005398969,0.0004796027,0.00003832782,0.000004620527,0.0001951723,0.00003201343,0.00001035616,0.0003715781],"genre_scores_gemma":[0.9961953,0.0001037485,0.002932551,0.00007233608,0.000009435595,0.0003712425,0.00007981494,0.000005312931,0.0002302728],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0152676,"threshold_uncertainty_score":0.08074373,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}