{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":104,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":104,"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"},"query_hash":"8954ed9680f4","filters":{"venue":"JMIR Biomedical Engineering"}},"results":[{"id":"W2975774002","doi":"10.2196/15025","title":"Immersive Virtual Reality in Health Care: Systematic Review of Technology and Disease States","year":2019,"lang":"en","type":"article","venue":"JMIR Biomedical Engineering","topic":"Virtual Reality Applications and Impacts","field":"Computer Science","cited_by":103,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"","keywords":"Virtual reality; Health care; Scopus; MEDLINE; Distraction; Phobias; Psychology; Medicine; Applied psychology; Multimedia; Medical education; Computer science; Human–computer interaction; Anxiety","retraction":null,"screen_n_in":null,"score":{"opus":0.005384389291779612,"gpt":0.2668969840972669,"spread":0.2615125948054873,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003123845,0.00008667746,0.0003514697,0.0002409069,0.00001187541,0.000009934114,0.0002811382,0.00004153735,0.000002359096],"category_scores_gemma":[0.0002632233,0.00007216774,0.00002730942,0.0008528954,0.00004062725,0.00009206319,0.0001365227,0.0001013657,0.000005276432],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007474178,"about_ca_system_score_gemma":0.0001189021,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002408198,"about_ca_topic_score_gemma":4.460374e-7,"domain_scores_codex":[0.998996,0.00002624914,0.0003963398,0.0001968972,0.0001986123,0.0001859471],"domain_scores_gemma":[0.9991699,0.00006957861,0.0000970757,0.0003912936,0.00003145808,0.0002407144],"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":[0.000005469252,0.0001563422,0.00009413117,0.844595,0.00003475643,0.000009613525,0.001368833,0.0001721004,0.0007132619,0.1468486,0.0004166029,0.005585278],"study_design_scores_gemma":[0.002725497,0.002085355,0.008902631,0.6426439,0.000065446,0.0000619672,0.001709387,0.3263613,0.0004119765,0.00235837,0.01119065,0.001483497],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05628597,0.1100924,0.756128,0.06867041,0.0003654489,0.007811515,0.0001421082,0.0004122806,0.0000918809],"genre_scores_gemma":[0.9959114,0.002467807,0.0009079012,0.0005484099,0.000007512613,0.0001216471,0.00001884163,0.00000709888,0.000009424492],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9396254,"threshold_uncertainty_score":0.2942915,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3044867568","doi":"10.2196/20921","title":"Current Status and Future Challenges of Sleep Monitoring Systems: Systematic Review","year":2020,"lang":"en","type":"article","venue":"JMIR Biomedical Engineering","topic":"Sleep and related disorders","field":"Psychology","cited_by":63,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"","keywords":"Software portability; Sleep (system call); Computer science; Position paper; Risk analysis (engineering); Medicine; World Wide Web","retraction":null,"screen_n_in":null,"score":{"opus":0.01587269084609739,"gpt":0.2849076889588633,"spread":0.2690349981127659,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001427494,0.000167925,0.0005217253,0.00008005009,0.00001638387,0.00000719656,0.000124546,0.0001484349,0.00002966739],"category_scores_gemma":[0.00007019388,0.0001294679,0.00006609767,0.0002552546,0.00003430845,0.00003210381,0.00004038342,0.0002758325,0.00002564624],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001633602,"about_ca_system_score_gemma":0.000008280901,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003223015,"about_ca_topic_score_gemma":1.933379e-8,"domain_scores_codex":[0.9987371,0.00004953652,0.0004571261,0.0002328441,0.0002479445,0.0002754547],"domain_scores_gemma":[0.9993202,0.00007037379,0.0001009616,0.0001825576,0.00002528332,0.0003005883],"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":[0.00001598091,0.0002098883,0.0001284581,0.9700893,0.001039679,0.00003685184,0.005757534,0.00004461725,0.0001661018,0.00507827,0.0006274392,0.01680591],"study_design_scores_gemma":[0.009971086,0.001786856,0.007022613,0.7145711,0.004495626,0.0002205052,0.02983771,0.01990719,0.00005762929,0.00002449343,0.2088284,0.003276789],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.00537093,0.9897183,0.0003332793,0.001268592,0.002182625,0.0008090556,0.000006773678,0.0001461453,0.0001642926],"genre_scores_gemma":[0.7395755,0.2584252,0.00007509242,0.00006571651,0.001339295,0.0004387264,0.00001071516,0.00006301098,0.000006726941],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.7342046,"threshold_uncertainty_score":0.5279546,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3046167810","doi":"10.2196/19623","title":"Fingerprint Biometric System Hygiene and the Risk of COVID-19 Transmission","year":2020,"lang":"en","type":"article","venue":"JMIR Biomedical Engineering","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":55,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"","keywords":"Biometrics; Fingerprint (computing); Fingerprint recognition; Computer science; Hygiene; Transmission (telecommunications); Infectious disease (medical specialty); Computer security; Coronavirus disease 2019 (COVID-19); Artificial intelligence; Medicine; Telecommunications; Pathology; Disease","retraction":null,"screen_n_in":null,"score":{"opus":0.01071971629337461,"gpt":0.2512982193956642,"spread":0.2405785031022896,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004636521,0.0001458441,0.0004215033,0.0002239675,0.00003835446,0.0000099041,0.0001496039,0.00008520953,0.00004392933],"category_scores_gemma":[0.001414162,0.00009112385,0.0001130378,0.001207488,0.0001928472,0.00002821683,0.00008517668,0.0002130026,0.000009526325],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005903387,"about_ca_system_score_gemma":0.00009594596,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003041523,"about_ca_topic_score_gemma":8.968812e-8,"domain_scores_codex":[0.998703,0.00005407638,0.0003562455,0.0002577878,0.0004282564,0.0002006146],"domain_scores_gemma":[0.9984431,0.0003360501,0.00008418897,0.0002409944,0.00003083574,0.0008648782],"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":[0.01074829,0.001558311,0.0279478,0.09080967,0.003753491,0.002005313,0.0137093,0.007292051,0.2123104,0.007338083,0.019845,0.6026823],"study_design_scores_gemma":[0.01512867,0.0005360768,0.04591297,0.000801,0.0003769855,0.0001517772,0.0003875392,0.6571435,0.001389105,0.00001214002,0.2776873,0.0004729492],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4961489,0.007705582,0.4718224,0.01956162,0.0003648611,0.002336138,0.0005303463,0.001228635,0.0003015155],"genre_scores_gemma":[0.9976793,0.000191902,0.001636294,0.0002639647,0.0001274274,0.00003625402,0.00003764595,0.00002081024,0.000006392393],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6498515,"threshold_uncertainty_score":0.3715923,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4281929536","doi":"10.2196/33771","title":"The Classification of Abnormal Hand Movement to Aid in Autism Detection: Machine Learning Study","year":2022,"lang":"en","type":"article","venue":"JMIR Biomedical Engineering","topic":"Autism Spectrum Disorder Research","field":"Neuroscience","cited_by":54,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"Islamic Development Bank; Weston Havens Foundation; Bill and Melinda Gates Foundation; Hartwell Foundation; Wu Tsai Neurosciences Institute, Stanford University; National Institutes of Health; National Science Foundation","keywords":"Autism; Computer science; Artificial intelligence; Set (abstract data type); Feature (linguistics); Flapping; Feature vector; Machine learning; Pattern recognition (psychology); Psychology; Developmental psychology; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.01803818076064211,"gpt":0.2818806283976813,"spread":0.2638424476370392,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006119506,0.00009295134,0.0001149257,0.0002777134,0.0003256739,0.00003418831,0.0003507393,0.00002316434,0.00008709586],"category_scores_gemma":[0.0002388511,0.00007937542,0.00002737565,0.00117162,0.00005919457,0.00004808926,0.0003749547,0.0005558046,0.000009775931],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001620574,"about_ca_system_score_gemma":0.0000314618,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007140465,"about_ca_topic_score_gemma":0.00003817716,"domain_scores_codex":[0.998211,0.0001309085,0.000282009,0.000263269,0.0007929886,0.0003198336],"domain_scores_gemma":[0.9994929,0.0001711893,0.00004404621,0.0001915865,0.000003133347,0.00009716359],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000116827,0.0007236848,0.002474219,0.00003372637,0.00001014471,0.00005340139,0.0029256,0.01978444,0.9458534,0.003278396,0.00001888325,0.02472724],"study_design_scores_gemma":[0.002294317,0.002586203,0.2687066,0.00002350716,0.000005306294,0.00002179409,0.000999021,0.6451007,0.03571456,0.0002120703,0.04397134,0.0003645715],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9918658,0.00004677929,0.004202958,0.002747333,0.0002109709,0.0007830482,0.000005082089,0.00006672075,0.00007135668],"genre_scores_gemma":[0.999214,0.000005379956,0.00002017159,0.00003070991,0.0000167726,0.0005440928,0.000001369196,0.00001647491,0.0001510191],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9101389,"threshold_uncertainty_score":0.3236836,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4313187564","doi":"10.2196/42709","title":"Mixed Reality Platforms in Telehealth Delivery: Scoping Review","year":2022,"lang":"en","type":"article","venue":"JMIR Biomedical Engineering","topic":"Telemedicine and Telehealth Implementation","field":"Medicine","cited_by":39,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"Science Foundation Ireland","keywords":"Telehealth; Augmented reality; Telemedicine; Virtual reality; Computer science; Mixed reality; Fidelity; Multimedia; Protocol (science); Videoconferencing; Medicine; Health care; Human–computer interaction","retraction":null,"screen_n_in":null,"score":{"opus":0.04941903067425123,"gpt":0.3637919003202182,"spread":0.3143728696459669,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001025947,0.0001578488,0.00047503,0.0003191767,0.0000880692,0.000003876686,0.0001091322,0.00005110311,0.0008322557],"category_scores_gemma":[0.0001684451,0.0001451255,0.00006437607,0.0009402591,0.00002710116,0.00006749531,0.0001100781,0.0005468158,0.000008740587],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003872226,"about_ca_system_score_gemma":0.0003523715,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001877526,"about_ca_topic_score_gemma":0.00002315106,"domain_scores_codex":[0.9977462,0.00002830129,0.000760845,0.0002855284,0.0006790151,0.0005000935],"domain_scores_gemma":[0.9991816,0.00009498416,0.0001042617,0.0002370616,0.00002587727,0.000356188],"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":[0.000726153,0.002348721,0.0256748,0.1931174,0.0002197851,0.002174186,0.002132985,0.0004537748,0.004856721,0.002212898,0.1369978,0.6290848],"study_design_scores_gemma":[0.02918519,0.007506405,0.2331549,0.1332778,0.000313953,0.002390064,0.001930367,0.03428164,0.000571451,0.0001815451,0.554973,0.002233605],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9433225,0.018305,0.003251616,0.02519477,0.001372473,0.007527366,0.00009380403,0.0006330293,0.0002994129],"genre_scores_gemma":[0.9830257,0.003890914,0.001916885,0.00820414,0.0004350594,0.00143967,0.0009835191,0.00005931832,0.00004484491],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6268512,"threshold_uncertainty_score":0.9112617,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2945726013","doi":"10.2196/13237","title":"The Effects of Titanium Implant Surface Topography on Osseointegration: Literature Review","year":2019,"lang":"en","type":"article","venue":"JMIR Biomedical Engineering","topic":"Bone Tissue Engineering Materials","field":"Engineering","cited_by":35,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"","keywords":"Osseointegration; Implant; Dentistry; Titanium; Dental implant; Materials science; Biomedical engineering; Medicine; Surgery","retraction":null,"screen_n_in":null,"score":{"opus":0.00173883350792291,"gpt":0.1969364216600964,"spread":0.1951975881521735,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002213118,0.0002614079,0.0003661902,0.00008892349,0.00002375339,0.00004043141,0.0002606197,0.0001381112,0.00003391477],"category_scores_gemma":[0.00009299076,0.0001836443,0.0001086015,0.0005880439,0.00002807466,0.00007290283,0.00002901593,0.0003020547,0.00007297305],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004039393,"about_ca_system_score_gemma":0.000009716559,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":9.663406e-7,"about_ca_topic_score_gemma":1.727137e-7,"domain_scores_codex":[0.9987801,0.00001798932,0.0003674429,0.0001759733,0.0003280554,0.0003304447],"domain_scores_gemma":[0.9990739,0.0003048374,0.00003685931,0.0004285927,0.00003783984,0.0001180082],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000286361,0.00008563827,0.00002386461,0.04499134,0.0003470985,0.0001281426,0.0002511617,0.01501547,0.8670948,0.004662166,0.06019643,0.007175229],"study_design_scores_gemma":[0.001733131,0.001048008,0.00218934,0.05436039,0.0001074211,0.0002611129,0.00002210674,0.04105756,0.1660647,0.00004943048,0.7314319,0.001674859],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6259611,0.3053845,0.01214737,0.001909329,0.03836315,0.007901442,0.0002279293,0.005394227,0.002710976],"genre_scores_gemma":[0.9688848,0.02747832,0.001916096,0.0001377512,0.0005673109,0.0001873736,0.000110463,0.000212234,0.000505647],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7010301,"threshold_uncertainty_score":0.7488796,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3045074988","doi":"10.2196/17355","title":"Measuring Heart Rate Variability in Free-Living Conditions Using Consumer-Grade Photoplethysmography: Validation Study","year":2020,"lang":"en","type":"article","venue":"JMIR Biomedical Engineering","topic":"Non-Invasive Vital Sign Monitoring","field":"Engineering","cited_by":33,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":false},"ca_institutions":"University of Waterloo; McMaster University; University of Toronto; Holland Bloorview Kids Rehabilitation Hospital","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Photoplethysmogram; Heart rate variability; Medicine; Heart rate; Computer science; Internal medicine; Blood pressure; Computer vision; Filter (signal processing)","retraction":null,"screen_n_in":null,"score":{"opus":0.03270483993088375,"gpt":0.2574169600762484,"spread":0.2247121201453646,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008908209,0.0003616804,0.0004433809,0.0003921573,0.00007870983,0.00008062371,0.0003181988,0.000175551,0.00006209251],"category_scores_gemma":[0.0008716545,0.0004326136,0.0001207014,0.001514925,0.00007504191,0.0003829948,0.0001537207,0.0006438272,0.00001471617],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002495345,"about_ca_system_score_gemma":0.00003983157,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008277973,"about_ca_topic_score_gemma":0.000003767255,"domain_scores_codex":[0.9976977,0.0001573674,0.0006068831,0.0004657005,0.0004568416,0.0006155806],"domain_scores_gemma":[0.998593,0.0005562618,0.00004178287,0.0003479445,0.00004268211,0.0004182837],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000005475193,0.00023069,0.02879342,0.0004149492,0.0001081015,0.00006669229,0.0009951326,0.05878264,0.9102829,0.00002664766,0.0001176135,0.0001756984],"study_design_scores_gemma":[0.005712045,0.0005109489,0.1702178,0.002207859,0.0002451869,0.0000798961,0.001631214,0.6089809,0.203812,0.0004529832,0.002337563,0.003811653],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9634026,0.0001663536,0.03363143,0.0001306752,0.0009019183,0.0008686962,0.00003409076,0.0008368854,0.00002739371],"genre_scores_gemma":[0.9967929,0.000007304941,0.002506686,0.0000306897,0.0003778849,0.0001792277,0.00001392918,0.00009051221,8.792245e-7],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.706471,"threshold_uncertainty_score":0.9998125,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3160852642","doi":"10.2196/22911","title":"Wearable Bioimpedance Monitoring: Viewpoint for Application in Chronic Conditions","year":2021,"lang":"en","type":"article","venue":"JMIR Biomedical Engineering","topic":"Non-Invasive Vital Sign Monitoring","field":"Engineering","cited_by":33,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"","keywords":"Wearable computer; Continuous monitoring; Wearable technology; Computer science; Reliability (semiconductor); Medicine; Remote patient monitoring; Intensive care medicine; Biomedical engineering; Embedded system; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.01025949189284459,"gpt":0.2649900530380211,"spread":0.2547305611451765,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000128046,0.0002099703,0.0002437284,0.0001885816,0.00004341308,0.00003529483,0.0001606477,0.0001595549,0.00001814716],"category_scores_gemma":[0.00008505234,0.0002483639,0.00008490392,0.0007054878,0.00003090447,0.0001517911,0.00004359325,0.0002701064,0.00004021062],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006293752,"about_ca_system_score_gemma":0.00007638932,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006277603,"about_ca_topic_score_gemma":0.000003090006,"domain_scores_codex":[0.9986463,0.000007905729,0.0003475942,0.000293592,0.0002087316,0.0004958967],"domain_scores_gemma":[0.9993511,0.0001326488,0.00002348721,0.0002636671,0.00004754153,0.0001815584],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00000175267,0.00003212401,0.0002841127,0.0005122064,0.00002460611,0.00001879798,0.00004581786,0.02647816,0.9671548,0.0003642772,0.0001458984,0.004937426],"study_design_scores_gemma":[0.001884067,0.0001084427,0.006599483,0.001362772,0.00002454717,0.00004322023,0.00009493272,0.1957103,0.7317851,0.0005611734,0.06084139,0.000984641],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2962633,0.008120449,0.6880597,0.000416182,0.003432679,0.001590204,0.0000967581,0.001612743,0.0004079186],"genre_scores_gemma":[0.9910696,0.0002471721,0.006081477,0.000009096268,0.00105396,0.001373361,0.00005112148,0.00007807123,0.00003610796],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6948063,"threshold_uncertainty_score":0.9999968,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2968157481","doi":"10.2196/13732","title":"Factors That Contribute to the Use of Stroke Self-Rehabilitation Technologies: A Review","year":2019,"lang":"en","type":"review","venue":"JMIR Biomedical Engineering","topic":"Stroke Rehabilitation and Recovery","field":"Medicine","cited_by":32,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"","keywords":"Rehabilitation; Telerehabilitation; Service delivery framework; Perspective (graphical); Health care; Narrative review; Stroke (engine); Rehabilitation counseling; Psychology; Medicine; Service (business); Physical medicine and rehabilitation; Computer science; Applied psychology; Physical therapy; Telemedicine; Artificial intelligence; Psychotherapist; Engineering; Business","retraction":null,"screen_n_in":null,"score":{"opus":0.06369128420982743,"gpt":0.3362302848257065,"spread":0.2725390006158791,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004056967,0.0004493662,0.002346335,0.0005931762,0.00002409127,0.00001708526,0.0002991989,0.0005342766,0.00004882225],"category_scores_gemma":[0.004285923,0.0002366689,0.001058114,0.0009563733,0.00009254205,0.00007008854,0.0001330277,0.000641267,0.00006176323],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000280186,"about_ca_system_score_gemma":0.0002477516,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003978109,"about_ca_topic_score_gemma":2.334764e-7,"domain_scores_codex":[0.9975848,0.00007375828,0.0009037681,0.0004148243,0.0006690332,0.0003538528],"domain_scores_gemma":[0.9956223,0.002990672,0.0002775536,0.0008090051,0.0001199122,0.0001805941],"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":[0.000006890148,0.0001780148,0.00007451087,0.2889404,0.0006320541,0.000004186198,0.000114791,0.000006747224,0.000009370007,0.00005364097,0.01316635,0.696813],"study_design_scores_gemma":[0.000194478,0.0003582554,0.0001071435,0.08354779,0.0007406655,0.00001271414,0.00004192752,0.0000668131,0.000001288682,2.390439e-7,0.9147282,0.0002004363],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00006478628,0.9909849,0.0008890284,0.001437882,0.0007234105,0.005200329,0.0003119637,0.0003801155,0.00000764095],"genre_scores_gemma":[0.0000348729,0.9966444,0.002133412,0.0001020655,0.00007425377,0.0005500773,0.0002191549,0.00005934584,0.0001824593],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9015619,"threshold_uncertainty_score":0.9651079,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3043897996","doi":"10.2196/16991","title":"Telerehabilitation for Patients With Knee Osteoarthritis: A Focused Review of Technologies and Teleservices","year":2020,"lang":"en","type":"review","venue":"JMIR Biomedical Engineering","topic":"Telemedicine and Telehealth Implementation","field":"Medicine","cited_by":29,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"Aalborg Universitetshospital; Aage og Johanne Louis-Hansens Fond; Aalborg Universitet","keywords":"Telerehabilitation; CINAHL; Telemedicine; Telehealth; eHealth; Rehabilitation; Medicine; MEDLINE; Service (business); Physical therapy; Health care; Computer science; Multimedia; Psychological intervention; Nursing","retraction":null,"screen_n_in":null,"score":{"opus":0.01610971258607015,"gpt":0.3223331462589112,"spread":0.306223433672841,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001453896,0.0003116302,0.001640666,0.0002854873,0.00002267266,0.000005661859,0.00009252874,0.000218015,0.0000225743],"category_scores_gemma":[0.0006174559,0.000214479,0.0001382513,0.0006329502,0.00008326287,0.00005786342,0.00004049417,0.0002599194,0.000001450304],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005928638,"about_ca_system_score_gemma":0.0001756493,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002112743,"about_ca_topic_score_gemma":5.938872e-7,"domain_scores_codex":[0.9981268,0.0000169695,0.0008693589,0.0003467657,0.0003822267,0.0002578764],"domain_scores_gemma":[0.9988569,0.0002984108,0.0003247824,0.0002185504,0.0001394414,0.0001619204],"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":[0.00001447156,0.00004002326,0.00001745542,0.3416436,0.00005825092,0.00000236981,0.00001743202,4.452122e-9,3.979714e-7,0.00001485916,0.0003942157,0.657797],"study_design_scores_gemma":[0.001701739,0.003727429,0.0001411675,0.1254666,0.000545983,0.000013582,0.00003358181,0.000007816456,7.855515e-7,0.000002723094,0.8681958,0.0001628391],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00007752359,0.9926668,0.0003459534,0.001017817,0.00006881261,0.005471529,0.000145177,0.0002004549,0.000005876906],"genre_scores_gemma":[0.00006214558,0.9897479,0.007428654,0.0001022323,0.000155599,0.00175969,0.000683532,0.00005778839,0.000002468487],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.8678016,"threshold_uncertainty_score":0.87462,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2945929497","doi":"10.2196/12291","title":"Determining the Accuracy of Oculus Touch Controllers for Motor Rehabilitation Applications Using Quantifiable Upper Limb Kinematics: Validation Study","year":2019,"lang":"en","type":"article","venue":"JMIR Biomedical Engineering","topic":"Stroke Rehabilitation and Recovery","field":"Medicine","cited_by":28,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"","keywords":"Kinematics; Physical medicine and rehabilitation; Computer science; Rehabilitation; Medicine; Physical therapy; Physics","retraction":null,"screen_n_in":null,"score":{"opus":0.01427499775994282,"gpt":0.3145336168299716,"spread":0.3002586190700287,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004118274,0.0001346084,0.0003467734,0.0002494878,0.00005546939,0.00001991217,0.00009996102,0.00009280506,0.00004680841],"category_scores_gemma":[0.001500452,0.00009475421,0.000191193,0.0003124041,0.00005471589,0.0001012581,0.00002495852,0.0001171136,0.000009009099],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000090023,"about_ca_system_score_gemma":0.00007638233,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006096471,"about_ca_topic_score_gemma":1.559382e-7,"domain_scores_codex":[0.998678,0.00002980998,0.0005407795,0.0002199196,0.0003401918,0.0001912735],"domain_scores_gemma":[0.9968782,0.002356989,0.0001544757,0.0003201524,0.0002020034,0.00008816796],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001195672,0.005268837,0.1869899,0.009851524,0.001054926,0.000001854218,0.007216517,0.02454855,0.7348078,0.001512593,0.0007416435,0.02681021],"study_design_scores_gemma":[0.01215912,0.004686391,0.1521828,0.0007963955,0.0003918127,0.000009996407,0.00627791,0.8089556,0.002360001,0.00005915058,0.01165796,0.0004629262],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9598986,0.0000293239,0.034071,0.0003248327,0.0003034808,0.005273306,0.0000150998,0.00005511936,0.00002926039],"genre_scores_gemma":[0.9829234,0.000002158492,0.0160156,0.00003165285,0.0001498796,0.0007329835,0.00003473011,0.00002714725,0.0000824093],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.784407,"threshold_uncertainty_score":0.3863965,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4297896480","doi":"10.2196/41782","title":"Telemonitoring of Home-Based Biking Exercise: Assessment of Wireless Interfaces","year":2022,"lang":"en","type":"article","venue":"JMIR Biomedical Engineering","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":20,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"National Heart, Lung, and Blood Institute","keywords":"Scalability; Bluetooth; Wireless; Computer science; Rehabilitation; Graphical user interface; Human–computer interaction; Physical therapy; Medicine; Telecommunications; Operating system","retraction":null,"screen_n_in":null,"score":{"opus":0.0217474853580399,"gpt":0.4073531831199162,"spread":0.3856056977618763,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001253675,0.000141892,0.0004244026,0.0003666195,0.000450989,0.000001835833,0.0003100818,0.000112575,0.0004251938],"category_scores_gemma":[0.00005754397,0.0001425896,0.00006299676,0.000755027,0.00005604081,0.00003450225,0.0002103685,0.001147444,0.000003368078],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002689796,"about_ca_system_score_gemma":0.0007001139,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000912968,"about_ca_topic_score_gemma":0.000001227668,"domain_scores_codex":[0.997533,0.000158822,0.0009758798,0.0002389733,0.0005711844,0.0005221676],"domain_scores_gemma":[0.9982855,0.0006442596,0.0003556436,0.0003282445,0.00008123345,0.0003051058],"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":[0.0005748905,0.004077191,0.1633253,0.0676905,0.000229836,0.0000338747,0.007379266,0.03266568,0.2199408,0.01763761,0.01405285,0.4723923],"study_design_scores_gemma":[0.007987078,0.001348287,0.1334757,0.005097776,0.0001053774,0.000005906786,0.007286271,0.3352298,0.004716083,0.0001175952,0.5035353,0.001094864],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9673252,0.000446455,0.02474068,0.0008419553,0.002696011,0.003261062,0.0001204517,0.0002515929,0.0003165572],"genre_scores_gemma":[0.9888332,0.00005083584,0.003081003,0.00006580706,0.0001617836,0.007683216,0.00004361633,0.00003306961,0.00004744812],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4894825,"threshold_uncertainty_score":0.5814635,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3010230791","doi":"10.2196/16620","title":"A Contact-Free, Ballistocardiography-Based Monitoring System (Emfit QS) for Measuring Nocturnal Heart Rate and Heart Rate Variability: Validation Study","year":2020,"lang":"en","type":"article","venue":"JMIR Biomedical Engineering","topic":"Heart Rate Variability and Autonomic Control","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"","keywords":"Heart rate variability; Heart rate; Nocturnal; Medicine; Ballistocardiography; Cardiology; Morning; Electrocardiography; Holter monitor; Internal medicine; Physical therapy; Blood pressure","retraction":null,"screen_n_in":null,"score":{"opus":0.02374285855204692,"gpt":0.2570240908858394,"spread":0.2332812323337925,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002531879,0.0003369134,0.0008644291,0.0002201391,0.0001397843,0.0001018535,0.0001453246,0.0001948036,0.00001255041],"category_scores_gemma":[0.001154367,0.0003140737,0.0002670573,0.0004744098,0.00005279372,0.000136896,0.0000794139,0.0004445697,0.000005648975],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000198452,"about_ca_system_score_gemma":0.0002070057,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002843304,"about_ca_topic_score_gemma":2.881939e-7,"domain_scores_codex":[0.997555,0.0002003939,0.0007152253,0.0006499041,0.0003797213,0.0004997793],"domain_scores_gemma":[0.9978673,0.0007140211,0.00007367171,0.0004442892,0.0001353628,0.0007653894],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008134789,0.0006397027,0.02984445,0.004695747,0.00077092,0.0000774587,0.001048291,0.003567393,0.9563997,0.0001693075,0.0002299606,0.001743523],"study_design_scores_gemma":[0.02093045,0.003049743,0.4213455,0.001349193,0.0006945166,0.00005929073,0.0006449365,0.5021196,0.01553863,0.00001875274,0.03322579,0.001023642],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9262384,0.00008971618,0.06382862,0.005136094,0.0006135249,0.003504251,0.00005165547,0.0005209814,0.00001676702],"genre_scores_gemma":[0.9951692,0.000001455325,0.003053605,0.0002500717,0.0009285914,0.0005205849,0.00002005366,0.00005207308,0.000004361992],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9408612,"threshold_uncertainty_score":0.9999312,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2763083873","doi":"10.2196/biomedeng.8179","title":"Heart Rate Monitoring Apps: Information for Engineers and Researchers About the New European Medical Devices Regulation 2017/745","year":2017,"lang":"en","type":"article","venue":"JMIR Biomedical Engineering","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":20,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"","keywords":"Parliament; Directive; Medical device; Member states; Medical research; Business; Political science; Medicine; European union; Computer science; Law; International trade","retraction":null,"screen_n_in":null,"score":{"opus":0.07436180532325429,"gpt":0.4492940473121578,"spread":0.3749322419889035,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.003402714,0.0001602852,0.0002065709,0.0001434234,0.001598134,0.00007400711,0.0004321988,0.0002409602,0.00005533541],"category_scores_gemma":[0.00254362,0.0001208965,0.00004536955,0.0001326842,0.0001193034,0.0003940008,0.0001720108,0.0007468413,0.00009789989],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001037104,"about_ca_system_score_gemma":0.000479491,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001415624,"about_ca_topic_score_gemma":0.00001067106,"domain_scores_codex":[0.9978589,0.0001246563,0.000643871,0.0002130217,0.0004656479,0.0006939506],"domain_scores_gemma":[0.9972812,0.0007992277,0.0002203722,0.0005181754,0.0001136134,0.001067406],"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":[0.0002914291,0.0001010977,0.007066195,0.007653141,0.0001185234,0.000005958695,0.007691102,0.0005734551,0.001366896,0.01718532,0.2755289,0.682418],"study_design_scores_gemma":[0.0009437303,0.00003876671,0.1596465,0.0004756085,0.000007162738,0.000002558583,0.0002322343,0.02351266,0.000008459222,0.00005189306,0.8149707,0.0001097884],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1539044,0.004177061,0.4207393,0.3685725,0.01076169,0.03146792,0.0001896925,0.002124077,0.008063313],"genre_scores_gemma":[0.9763091,0.001055388,0.006453283,0.002173961,0.005869172,0.006912354,0.0001777369,0.00009284703,0.0009561469],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8224047,"threshold_uncertainty_score":0.9997017,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3025135801","doi":"10.2196/17467","title":"Innovation in Pediatric Medical Devices: Proceedings From The West Coast Consortium for Technology &amp; Innovation in Pediatrics 2019 Annual Stakeholder Summit","year":2020,"lang":"en","type":"article","venue":"JMIR Biomedical Engineering","topic":"Pharmaceutical studies and practices","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"","keywords":"Summit; Stakeholder; Medicine; Stakeholder engagement; Investment (military); Business; Family medicine; Pediatrics; Public relations; Political science","retraction":null,"screen_n_in":null,"score":{"opus":0.05887481376263513,"gpt":0.3307775873055228,"spread":0.2719027735428877,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008371403,0.0002125272,0.0003754681,0.000542695,0.0000494767,0.00002467658,0.000231893,0.0003854618,0.00008678709],"category_scores_gemma":[0.006456702,0.0001613126,0.00003122302,0.00650094,0.00009475177,0.0001807256,0.0001472593,0.0009973532,0.00001848907],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000855719,"about_ca_system_score_gemma":0.0001786544,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004342241,"about_ca_topic_score_gemma":0.00004775032,"domain_scores_codex":[0.9976032,0.00001210945,0.0009594653,0.0003747953,0.0006134268,0.0004369728],"domain_scores_gemma":[0.9986809,0.0006079294,0.0001943976,0.00009668373,0.0002633774,0.0001567231],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0008045217,0.0008732265,0.8974003,0.001978036,0.0001242285,0.00009723588,0.002854852,0.00006186758,0.002544358,0.003886412,0.06607547,0.02329946],"study_design_scores_gemma":[0.007583071,0.0004664456,0.2491199,0.0002505847,0.0001618889,0.00001714305,0.001871201,0.01211923,0.0001176946,0.000112363,0.7276065,0.0005740537],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.915979,0.0008194468,0.002963158,0.07870284,0.0002631066,0.0009820954,0.000100204,0.0001489748,0.00004114712],"genre_scores_gemma":[0.9928468,0.0004087208,0.00122039,0.003474274,0.00153714,0.0002321014,0.0002363345,0.00003345081,0.00001082895],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.661531,"threshold_uncertainty_score":0.7729741,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4290975460","doi":"10.2196/36618","title":"Noncontact Longitudinal Respiratory Rate Measurements in Healthy Adults Using Radar-Based Sleep Monitor (Somnofy): Validation Study","year":2022,"lang":"en","type":"article","venue":"JMIR Biomedical Engineering","topic":"Non-Invasive Vital Sign Monitoring","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"","keywords":"Medicine; Supine position; Respiratory rate; Sleep (system call); Mood; Heart rate; Audiology; Anesthesia; Internal medicine; Blood pressure; Computer science","retraction":null,"screen_n_in":null,"score":{"opus":0.03916778532118809,"gpt":0.2852182289418858,"spread":0.2460504436206977,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001031742,0.0004171209,0.0004392813,0.0008240559,0.0001851903,0.00005593834,0.0003864244,0.0001154472,0.00006209293],"category_scores_gemma":[0.000100431,0.0004999491,0.000101477,0.001327886,0.00002749699,0.000259623,0.0001498064,0.0007850031,0.00001093112],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001799652,"about_ca_system_score_gemma":0.00009727255,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001410547,"about_ca_topic_score_gemma":0.00001224755,"domain_scores_codex":[0.9967155,0.0001656918,0.0007504671,0.0005269267,0.001081482,0.0007598811],"domain_scores_gemma":[0.9989973,0.0001398492,0.00008799154,0.0003856853,0.00005276717,0.0003364467],"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":[0.000625252,0.001072325,0.1295955,0.0005741818,0.0001701169,0.0003948336,0.0006318477,0.4671469,0.3958172,0.000003414612,0.00007081067,0.003897638],"study_design_scores_gemma":[0.03129892,0.007378636,0.1701343,0.001180426,0.0001657141,0.00004707984,0.001957086,0.6964152,0.08407178,0.00001402753,0.003120382,0.004216492],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9874514,0.0002443269,0.008224539,0.00002187557,0.002362658,0.001169642,0.00002192558,0.0004857605,0.00001785703],"genre_scores_gemma":[0.9975632,0.000001364864,0.001198011,0.00002845825,0.0005093123,0.0005432051,0.00002507843,0.0001300262,0.000001274604],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3117454,"threshold_uncertainty_score":0.9997452,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4309753944","doi":"10.2196/41003","title":"Detection of Mental Fatigue in the General Population: Feasibility Study of Keystroke Dynamics as a Real-world Biomarker","year":2022,"lang":"en","type":"article","venue":"JMIR Biomedical Engineering","topic":"Sleep and Work-Related Fatigue","field":"Psychology","cited_by":18,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"Horizon 2020 Framework Programme; Ministerio de Ciencia e Innovación","keywords":"Keystroke dynamics; Computer science; Keystroke logging; Population; Artificial intelligence; Medicine; Computer security","retraction":null,"screen_n_in":null,"score":{"opus":0.02655088657659846,"gpt":0.3361409708652715,"spread":0.3095900842886731,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005299628,0.0001241342,0.0002065599,0.0003420182,0.00005957429,0.00000471709,0.0002276013,0.00007602455,0.0002974234],"category_scores_gemma":[0.0000232372,0.0001058653,0.00006994008,0.001146507,0.00004043534,0.00003032016,0.00007977059,0.0003399352,0.000001746483],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001963481,"about_ca_system_score_gemma":0.00001036707,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003013909,"about_ca_topic_score_gemma":0.0004055565,"domain_scores_codex":[0.9984534,0.000187759,0.0004915049,0.0002335546,0.0004344526,0.0001992727],"domain_scores_gemma":[0.999429,0.00009045545,0.0001091295,0.0003075827,0.00001384875,0.0000499699],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00133962,0.01466133,0.824583,0.000120104,0.001017367,0.0002000934,0.03268875,0.01125936,0.01334616,0.005345382,0.0005771967,0.09486167],"study_design_scores_gemma":[0.002483466,0.0008511179,0.9686706,0.00003454899,0.00003413426,0.00001330276,0.00421782,0.02336164,0.000042552,0.00001656761,0.00009585325,0.000178404],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9976621,0.00003119548,0.000325868,0.00008665687,0.0007138753,0.0007181062,0.00002728508,0.00003857179,0.0003963171],"genre_scores_gemma":[0.9995555,9.335351e-7,0.00004524322,0.00001230161,0.00004217251,0.0002253048,0.00007161867,0.00001567869,0.00003121865],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1440876,"threshold_uncertainty_score":0.4556149,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2545221125","doi":"10.2196/biomedeng.6401","title":"A Six-Step Framework on Biomedical Signal Analysis for Tackling Noncommunicable Diseases: Current and Future Perspectives","year":2016,"lang":"en","type":"article","venue":"JMIR Biomedical Engineering","topic":"ECG Monitoring and Analysis","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"","keywords":"mHealth; Scope (computer science); Health care; Computer science; Risk analysis (engineering); The Internet; Robustness (evolution); Data science; Knowledge management; Process management; Medicine; Business; Political science; World Wide Web","retraction":null,"screen_n_in":null,"score":{"opus":0.008487668346988072,"gpt":0.2959716978525556,"spread":0.2874840295055675,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002322645,0.0002770479,0.0006266521,0.0006817108,0.000117656,0.0000346169,0.0001741707,0.0002372168,0.0001315186],"category_scores_gemma":[0.0004169293,0.0001773385,0.0004138827,0.001100792,0.0001779216,0.00006138576,0.00008419358,0.0003901886,0.000008267053],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001438965,"about_ca_system_score_gemma":0.00005887164,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005380512,"about_ca_topic_score_gemma":3.805261e-7,"domain_scores_codex":[0.9981282,0.00002703693,0.0003550385,0.0004865532,0.0005388259,0.0004643205],"domain_scores_gemma":[0.9980683,0.0007287535,0.00006877066,0.0004334916,0.00008238964,0.0006182665],"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":[0.00124556,0.005319273,0.03955946,0.002366997,0.01116633,0.0002019365,0.003050688,0.0002460415,0.01985705,0.005227691,0.004484211,0.9072747],"study_design_scores_gemma":[0.009389809,0.003744298,0.05804834,0.008384044,0.008498687,0.00004827797,0.003445428,0.2912121,0.0004903937,0.0003176644,0.6141275,0.002293442],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2177847,0.01020232,0.7537856,0.0153884,0.00101153,0.0008569211,0.0002665362,0.0006594495,0.00004462507],"genre_scores_gemma":[0.9816599,0.000810424,0.01330797,0.00005083109,0.003821372,0.0001656899,0.00005781803,0.00004438929,0.00008160241],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9049813,"threshold_uncertainty_score":0.7231652,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4391896879","doi":"10.2196/56245","title":"Investigation of Deepfake Voice Detection Using Speech Pause Patterns: Algorithm Development and Validation","year":2024,"lang":"en","type":"article","venue":"JMIR Biomedical Engineering","topic":"Speech Recognition and Synthesis","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"Glycemic Index Laboratories","funders":"","keywords":"Preprint; Computer science; Speech recognition; World Wide Web","retraction":null,"screen_n_in":null,"score":{"opus":0.02409744204276851,"gpt":0.2441410869546239,"spread":0.2200436449118554,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000247905,0.00009383222,0.00009418025,0.0002858853,0.00003103048,0.00008604331,0.00009750642,0.0000787005,0.000007017633],"category_scores_gemma":[0.000040351,0.00008962306,0.000022228,0.0004163375,0.00001943493,0.0002814355,0.00005557096,0.00008946525,0.000008230233],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005858283,"about_ca_system_score_gemma":0.00003874386,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001155717,"about_ca_topic_score_gemma":0.000001140458,"domain_scores_codex":[0.9991549,0.00001683009,0.0002290659,0.0002111744,0.0002627893,0.0001252877],"domain_scores_gemma":[0.9996661,0.00007999557,0.00003049162,0.00009244993,0.0000308872,0.0001000586],"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":[4.436139e-7,0.000005794835,0.00004108694,0.0001575099,0.00001778619,0.00001524382,0.0003489585,0.00001052418,0.06652493,0.00003968318,0.000003241573,0.9328348],"study_design_scores_gemma":[0.00007524445,0.00001744454,0.001600654,0.0002301286,0.000005630854,0.00005591098,0.00001305765,0.666294,0.3302898,0.00004856998,0.001260624,0.0001089215],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3976344,0.00004097187,0.6018562,0.00003872496,0.0002336244,0.00006438095,0.000001338619,0.0001274023,0.000003035957],"genre_scores_gemma":[0.6648999,0.00000980112,0.3349307,0.00001975009,0.00009618096,0.0000188302,0.000007272789,0.00001108103,0.000006459938],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9327258,"threshold_uncertainty_score":0.3654723,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3170910671","doi":"10.2196/26942","title":"Using Medical Device Standards for Design and Risk Management of Immersive Virtual Reality for At-Home Therapy and Remote Patient Monitoring","year":2021,"lang":"en","type":"article","venue":"JMIR Biomedical Engineering","topic":"Virtual Reality Applications and Impacts","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"","keywords":"Virtual reality; Computer science; Process (computing); Set (abstract data type); Human–computer interaction","retraction":null,"screen_n_in":null,"score":{"opus":0.04682139783116929,"gpt":0.330447281340795,"spread":0.2836258835096257,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006879528,0.000126513,0.0002067544,0.00006430638,0.0001085006,0.0000377751,0.0001663344,0.00009671223,0.000001843214],"category_scores_gemma":[0.0001370849,0.0001156024,0.0000461233,0.0002512518,0.00006080767,0.0001022336,0.0002210532,0.0000804647,7.59556e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001095503,"about_ca_system_score_gemma":0.0001030457,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001805147,"about_ca_topic_score_gemma":3.755607e-7,"domain_scores_codex":[0.9986444,0.00003160179,0.0002841656,0.0003181243,0.0004737999,0.0002479668],"domain_scores_gemma":[0.9989608,0.0003258745,0.00008307044,0.0002343567,0.0001250404,0.0002708653],"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":[0.0001031232,0.000111821,0.00002634893,0.0004198581,0.0002256921,0.00001438443,0.00104689,0.001378536,0.008977412,0.006641069,0.0001186367,0.9809362],"study_design_scores_gemma":[0.001724362,0.0005121758,0.001193384,0.0003692281,0.00002816194,0.00002642753,0.0001901103,0.9701768,0.01182625,0.0005870202,0.01311313,0.0002529972],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1116676,0.000559126,0.8868661,0.0002256327,0.0001129105,0.0004835411,0.00005586066,0.00002531733,0.000003984763],"genre_scores_gemma":[0.3763887,0.002248919,0.6210826,0.00004290416,0.00009926114,0.00009503992,0.00001236919,0.00002317407,0.000006979953],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9806832,"threshold_uncertainty_score":0.4714131,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3006448441","doi":"10.2196/14389","title":"Longitudinal Magnetic Resonance Imaging as a Potential Correlate in the Diagnosis of Alzheimer Disease: Exploratory Data Analysis","year":2020,"lang":"en","type":"article","venue":"JMIR Biomedical Engineering","topic":"Dementia and Cognitive Impairment Research","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"National Institutes of Health","keywords":"Clinical Dementia Rating; Dementia; Magnetic resonance imaging; Neuroimaging; Medicine; Alzheimer's disease; Longitudinal study; Disease; Psychology; Psychiatry; Radiology; Internal medicine; Pathology","retraction":null,"screen_n_in":null,"score":{"opus":0.03217284643319224,"gpt":0.3158542018947447,"spread":0.2836813554615525,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003344916,0.0001409491,0.0002776607,0.0002555523,0.00002853228,0.00002423661,0.0003608449,0.00003693707,0.0003758127],"category_scores_gemma":[0.0002473337,0.0001051565,0.0001126599,0.001512954,0.0001346207,0.0001202373,0.0002444592,0.000293009,0.00002288622],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001457427,"about_ca_system_score_gemma":0.00008787655,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002111286,"about_ca_topic_score_gemma":6.024571e-7,"domain_scores_codex":[0.9981278,0.0000532306,0.0003202756,0.0003786234,0.0008070332,0.0003130925],"domain_scores_gemma":[0.999103,0.00008075367,0.0000365302,0.0004008365,0.00004679552,0.0003320539],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003840021,0.0008974973,0.9411544,0.0003206825,0.0005136556,0.003225117,0.0007470833,0.0001791832,0.001551428,0.00005856092,0.003032456,0.04793591],"study_design_scores_gemma":[0.0009998644,0.0001647686,0.8379694,0.0001236391,0.0008855111,0.0000105934,0.0001822726,0.1546799,0.00007722128,0.000003458383,0.004789925,0.0001135307],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9435548,0.03003623,0.009416303,0.01491126,0.0001602127,0.001411962,0.0001768221,0.0001250857,0.0002073357],"genre_scores_gemma":[0.9988294,0.0001987934,0.000154577,0.0003434914,0.0001255806,0.0001525874,0.0001702419,0.00001532063,0.000009973554],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1545007,"threshold_uncertainty_score":0.4288158,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4214541916","doi":"10.2196/31079","title":"Democratizing Global Health Care Through Scalable Emergent (Beyond the Mobile) Wireless Technologies","year":2022,"lang":"en","type":"article","venue":"JMIR Biomedical Engineering","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":15,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"Novartis","keywords":"Firmware; Software deployment; Computer science; Cloud computing; Mobile technology; Scalability; Internet privacy; Variety (cybernetics); Mobile phone; Mobile device; Computer security; Telecommunications; World Wide Web","retraction":null,"screen_n_in":null,"score":{"opus":0.01537423219711746,"gpt":0.3844119805328531,"spread":0.3690377483357356,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.00074077,0.0002571182,0.0003961947,0.00009455268,0.00328063,0.00001019113,0.0006516119,0.0002026561,0.0004255305],"category_scores_gemma":[0.00007613266,0.0002030527,0.00009154719,0.001441808,0.0001180233,0.000070796,0.0006637273,0.001536584,0.00008295527],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001559215,"about_ca_system_score_gemma":0.001316565,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000307188,"about_ca_topic_score_gemma":0.0000456789,"domain_scores_codex":[0.9963203,0.0002141862,0.0009497112,0.0004863916,0.0006704759,0.001358907],"domain_scores_gemma":[0.9983814,0.0002437124,0.0002606318,0.000674988,0.0000754478,0.0003638262],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00009699607,0.0004972909,0.002441342,0.00498487,0.00009823122,0.00002566483,0.0118561,0.004284646,0.0004095214,0.08659618,0.4513101,0.4373991],"study_design_scores_gemma":[0.0005465867,0.0001893733,0.0004485323,0.0000670967,0.000007232085,0.00001100092,0.01666411,0.003200219,0.000006611202,0.0003819257,0.9782932,0.0001841548],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.2646069,0.1011172,0.160362,0.3408912,0.0263227,0.07541448,0.003353548,0.01660511,0.01132685],"genre_scores_gemma":[0.8877147,0.001284052,0.003240921,0.00814337,0.0006445562,0.0982921,0.0003493143,0.00008399787,0.0002470327],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6231077,"threshold_uncertainty_score":0.998017,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2774982771","doi":"10.2196/biomedeng.8333","title":"Measurement of Skin Induration Size Using Smartphone Images and Photogrammetric Reconstruction: Pilot Study","year":2017,"lang":"en","type":"article","venue":"JMIR Biomedical Engineering","topic":"Mycobacterium research and diagnosis","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"","keywords":"Tuberculin; Medicine; Skin test; Tuberculosis; Dermatology; Latent tuberculosis; Photogrammetry; Artificial intelligence; Mycobacterium tuberculosis; Pathology; Computer science","retraction":null,"screen_n_in":null,"score":{"opus":0.04771764156472056,"gpt":0.3123209073334248,"spread":0.2646032657687042,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005281782,0.0001177455,0.0002666018,0.0002430121,0.00009679111,0.00005568692,0.0000847757,0.00005448354,0.00006823672],"category_scores_gemma":[0.001801918,0.0001007267,0.00003263654,0.0002214924,0.0001054532,0.0001199126,0.00007888588,0.0001864441,0.000001898687],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009004491,"about_ca_system_score_gemma":0.00007070633,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003505897,"about_ca_topic_score_gemma":0.000007099941,"domain_scores_codex":[0.9986839,0.00001999421,0.0002674547,0.0001963346,0.0006148196,0.0002174393],"domain_scores_gemma":[0.9991373,0.00006851589,0.00009085371,0.0002883747,0.0001358616,0.0002791175],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0002983344,0.001425201,0.1610037,0.0006283788,0.00022099,0.00007463824,0.0001363604,0.000003267377,0.7535731,0.000003151521,0.0001268702,0.08250601],"study_design_scores_gemma":[0.002707543,0.00263663,0.9734913,0.0003417145,0.00005695042,0.0000854497,0.0001066365,0.001575494,0.01873291,0.000002170507,0.0001376822,0.00012557],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9980202,0.0001368435,0.0008646482,0.0001329565,0.0002073301,0.0005475321,0.000004854175,0.00003274836,0.0000529063],"genre_scores_gemma":[0.9979912,0.00004227036,0.001677441,0.000007220861,0.0002057833,0.00005423748,0.000001831335,0.00001369613,0.000006327199],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8124875,"threshold_uncertainty_score":0.4107517,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3012816200","doi":"10.2196/18158","title":"Heart Rate and Oxygen Saturation Monitoring With a New Wearable Wireless Device in the Intensive Care Unit: Pilot Comparison Trial","year":2020,"lang":"en","type":"article","venue":"JMIR Biomedical Engineering","topic":"Non-Invasive Vital Sign Monitoring","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"","keywords":"Medicine; Heart rate; Oxygen saturation; Intensive care unit; Adverse effect; Intensive care; Continuous monitoring; Coronary care unit; Clinical trial; Cardiology; Emergency medicine; Anesthesia; Internal medicine; Intensive care medicine; Oxygen; Blood pressure","retraction":null,"screen_n_in":null,"score":{"opus":0.03401587904812729,"gpt":0.2687862516253795,"spread":0.2347703725772522,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001278586,0.0002711802,0.0003316813,0.0001215593,0.00005509456,0.0001083426,0.0002026773,0.0001044351,0.000003059984],"category_scores_gemma":[0.0001165263,0.0002148731,0.00003177207,0.000728767,0.00003816128,0.0002036267,0.00005336106,0.0005848148,0.000008928442],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008605028,"about_ca_system_score_gemma":0.00003866291,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000718154,"about_ca_topic_score_gemma":0.00001072542,"domain_scores_codex":[0.9986832,0.00003366092,0.0003139988,0.0002644763,0.0003227328,0.0003820019],"domain_scores_gemma":[0.9992788,0.0001881109,0.0000306378,0.0001541212,0.00007316782,0.0002751716],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003226364,0.00007676531,0.01376487,0.001544526,0.0001939643,0.0001702255,0.03372007,0.06306577,0.8746504,0.00005337463,0.0006504583,0.008883191],"study_design_scores_gemma":[0.1220746,0.01136829,0.1549085,0.008060656,0.0003512477,0.0002161862,0.08156723,0.3721591,0.2070843,0.00004590883,0.03611748,0.006046563],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9904048,0.0009483756,0.006508465,0.000591705,0.0004992475,0.0007254932,0.000003432542,0.0002882179,0.00003021686],"genre_scores_gemma":[0.99781,0.00002649184,0.0008005644,0.00008614462,0.001117,0.00009231586,0.000009448635,0.00005581371,0.000002222407],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6675661,"threshold_uncertainty_score":0.876227,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4400173011","doi":"10.2196/59459","title":"Assessing the Accuracy of Smartwatch-Based Estimation of Maximum Oxygen Uptake Using the Apple Watch Series 7: Validation Study","year":2024,"lang":"en","type":"article","venue":"JMIR Biomedical Engineering","topic":"Cardiovascular and exercise physiology","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"","keywords":"Intraclass correlation; VO2 max; Cardiorespiratory fitness; Smartwatch; Statistics; Mathematics; Gold standard (test); Limits of agreement; Medicine; Physical therapy; Animal science; Heart rate; Computer science; Reproducibility; Nuclear medicine; Internal medicine; Blood pressure","retraction":null,"screen_n_in":null,"score":{"opus":0.02277524894618526,"gpt":0.3278914146398342,"spread":0.305116165693649,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006034881,0.0001240185,0.0003198216,0.00008869224,0.00005054395,0.00003444019,0.0001061499,0.00007112201,0.00002078468],"category_scores_gemma":[0.0001861082,0.00007039151,0.0001874104,0.0005068276,0.0001046271,0.0001293926,0.00005202303,0.0001872392,0.000002032237],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004279213,"about_ca_system_score_gemma":0.0001113124,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005815014,"about_ca_topic_score_gemma":3.604651e-7,"domain_scores_codex":[0.9988791,0.00004438073,0.0003531823,0.0001648728,0.00040116,0.0001573053],"domain_scores_gemma":[0.999318,0.0002073763,0.00005343261,0.000319951,0.0000538094,0.00004743605],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003112401,0.0007368077,0.0002922902,0.004213423,0.001473664,0.00008015858,0.005525315,0.2405183,0.6556653,0.0002055013,0.0005562904,0.09042168],"study_design_scores_gemma":[0.0008504035,0.0002274526,0.01755808,0.0006438235,0.0005588329,0.00007675486,0.001431781,0.9461694,0.03032089,0.0000802162,0.001920844,0.0001615354],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9119805,0.0002278833,0.08606379,0.0007375668,0.0002922307,0.0006108952,0.000006553872,0.00007034753,0.00001019726],"genre_scores_gemma":[0.998031,0.000006511211,0.001647778,0.00001152289,0.0001645098,0.00005381242,0.00005726121,0.00002244837,0.000005204357],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.705651,"threshold_uncertainty_score":0.2870483,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3024363903","doi":"10.2196/13611","title":"Robust Feature Engineering for Parkinson Disease Diagnosis: New Machine Learning Techniques","year":2020,"lang":"en","type":"article","venue":"JMIR Biomedical Engineering","topic":"Voice and Speech Disorders","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"Australian National University; Australian Government","keywords":"Phonation; Computer science; Support vector machine; Feature (linguistics); Data set; Set (abstract data type); Artificial intelligence; Feature engineering; Machine learning; Pattern recognition (psychology); Deep learning; Medicine; Audiology","retraction":null,"screen_n_in":null,"score":{"opus":0.01736119203992213,"gpt":0.2454880148594546,"spread":0.2281268228195325,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00009634978,0.0002906944,0.0003757237,0.000159781,0.00004866491,0.00003334695,0.000147008,0.0001968179,0.00008012805],"category_scores_gemma":[0.0008656341,0.0002660545,0.0002056456,0.0004290685,0.00002182752,0.00009531713,0.00005964884,0.0005793854,0.00001235875],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005628604,"about_ca_system_score_gemma":0.00008664213,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008685608,"about_ca_topic_score_gemma":5.670457e-7,"domain_scores_codex":[0.9985602,0.000006444399,0.0002467301,0.0003891117,0.0003419776,0.0004554698],"domain_scores_gemma":[0.9984974,0.00009312358,0.0000407912,0.0001646159,0.00003235471,0.001171693],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002760066,0.001778815,0.04373768,0.02025682,0.001671945,0.002022567,0.003280022,0.03784204,0.1285722,0.0009636608,0.3904501,0.3666641],"study_design_scores_gemma":[0.001060523,0.0003447573,0.002029613,0.0003814758,0.00008777541,0.000009378927,0.00002105691,0.1598209,0.001722091,0.000002834969,0.8342282,0.0002913362],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05005072,0.01661822,0.7497742,0.1693989,0.0008755568,0.005635263,0.000156732,0.007330812,0.0001595772],"genre_scores_gemma":[0.7558068,0.002172797,0.2204868,0.00710264,0.008188946,0.002702754,0.001385597,0.000639679,0.001513952],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7057561,"threshold_uncertainty_score":0.9999791,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4391840120","doi":"10.2196/50175","title":"Enhancing Energy Efficiency in Telehealth Internet of Things Systems Through Fog and Cloud Computing Integration: Simulation Study","year":2024,"lang":"en","type":"article","venue":"JMIR Biomedical Engineering","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"University of Victoria","funders":"","keywords":"Preprint; Cloud computing; Internet of Things; Computer science; Telehealth; Fog computing; Embedded system; Operating system; Telemedicine; World Wide Web; Health care","retraction":null,"screen_n_in":null,"score":{"opus":0.01017767652013911,"gpt":0.2706060941609583,"spread":0.2604284176408191,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006970394,0.0001636542,0.0002648964,0.0003106128,0.00004223188,0.0001956452,0.0003010144,0.0000863004,4.60711e-7],"category_scores_gemma":[0.00007259439,0.0001446488,0.00003465761,0.0009440027,0.00002827801,0.0004315774,0.000257537,0.0002544633,0.000001417407],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009359745,"about_ca_system_score_gemma":0.000060906,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000331548,"about_ca_topic_score_gemma":0.000001932656,"domain_scores_codex":[0.9983582,0.00004896981,0.0005793103,0.0003847238,0.000331038,0.0002977223],"domain_scores_gemma":[0.9992493,0.0004012839,0.00006671299,0.0001699119,0.00003450199,0.00007826678],"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":[0.00002948306,0.001310033,0.001268971,0.00478322,0.0001957042,0.0004494895,0.2871,0.1683614,0.01129705,0.05405654,0.0007454409,0.4704027],"study_design_scores_gemma":[0.0001810941,0.000166596,0.0002815147,0.0008446352,0.000002809446,0.00001313744,0.00021606,0.9967003,0.0002570557,0.00003867655,0.00116198,0.0001360838],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2020536,0.0005686195,0.7909443,0.00004883716,0.005972034,0.0001631657,5.417201e-8,0.0002129858,0.00003641644],"genre_scores_gemma":[0.9942818,0.000003462923,0.00468359,0.00002180705,0.0009765427,0.000007354713,0.000002028621,0.00001327684,0.00001010018],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.828339,"threshold_uncertainty_score":0.5898606,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4317522925","doi":"10.2196/43726","title":"An Algorithm to Classify Real-World Ambulatory Status From a Wearable Device Using Multimodal and Demographically Diverse Data: Validation Study","year":2023,"lang":"en","type":"article","venue":"JMIR Biomedical Engineering","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"Verily Life Sciences","keywords":"Generalizability theory; Biometrics; Wearable computer; Computer science; Ground truth; Artificial intelligence; Wearable technology; Machine learning; Set (abstract data type); Algorithm; Data set; Data mining; Statistics; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.05985076518709303,"gpt":0.3398835450617325,"spread":0.2800327798746395,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007900223,0.0002132275,0.0002899705,0.0007013641,0.0001326439,0.0002859733,0.0006847713,0.0001032245,0.000009265204],"category_scores_gemma":[0.0001009542,0.0002224277,0.00003198753,0.002037069,0.0000369137,0.001094018,0.0008085585,0.0002489034,0.00003681669],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009556888,"about_ca_system_score_gemma":0.00008455864,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002014919,"about_ca_topic_score_gemma":0.0001433814,"domain_scores_codex":[0.9975583,0.0001394919,0.0003564419,0.0008332189,0.0006483276,0.0004642261],"domain_scores_gemma":[0.9981059,0.000331698,0.00007007766,0.0008223689,0.00007239419,0.000597561],"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":[0.00005353423,0.001296034,0.03701944,0.0001709908,0.0004781887,0.0005693783,0.006108652,0.00359823,0.07490668,0.00005988227,0.0006777811,0.8750612],"study_design_scores_gemma":[0.0005827874,0.0001010021,0.1268718,0.00009073276,0.00001581526,0.000003739517,0.0002626932,0.8703565,0.00006973033,0.000008260989,0.001377701,0.0002592359],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6123968,0.0000123016,0.3859487,0.00009235254,0.0004156355,0.000471153,0.00008705143,0.0005722207,0.0000037972],"genre_scores_gemma":[0.9568673,0.000007910436,0.04267285,0.00004409444,0.0002140646,0.00005706205,0.0001005414,0.00002682401,0.000009328022],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.874802,"threshold_uncertainty_score":0.9070337,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3157541674","doi":"10.2196/26332","title":"Virtual Reality–Guided Meditation for Chronic Pain in Patients With Cancer: Exploratory Analysis of Electroencephalograph Activity","year":2021,"lang":"en","type":"article","venue":"JMIR Biomedical Engineering","topic":"Mindfulness and Compassion Interventions","field":"Psychology","cited_by":13,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":false},"ca_institutions":"Fraser Health; University of British Columbia; Surrey Memorial Hospital; Simon Fraser University","funders":"Simon Fraser University; Lotte and John Hecht Memorial Foundation","keywords":"Meditation; Medicine; Cancer; Virtual reality; Psychology; Physical therapy; Computer science; Human–computer interaction; Internal medicine","retraction":null,"screen_n_in":null,"score":{"opus":0.01715056772425955,"gpt":0.3167059754155813,"spread":0.2995554076913217,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000291051,0.0001009519,0.0002769065,0.0004570736,0.00002134625,0.000006121853,0.00008997932,0.00008774055,0.0008979],"category_scores_gemma":[0.0000663538,0.00008990983,0.0001366928,0.00154025,0.00004062419,0.00005260369,0.00001651545,0.000119756,6.0794e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009660547,"about_ca_system_score_gemma":0.00007150457,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005638032,"about_ca_topic_score_gemma":0.0001825625,"domain_scores_codex":[0.9989542,0.00008546228,0.0002849227,0.0002364758,0.0002178177,0.0002211086],"domain_scores_gemma":[0.9994064,0.0001385754,0.00009002486,0.0001806934,0.0001011453,0.00008319048],"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":[0.001471541,0.01062093,0.1014576,0.001203902,0.01202898,0.00007330185,0.004525164,0.02998249,0.008647264,0.04023994,0.03069556,0.7590533],"study_design_scores_gemma":[0.005303102,0.002025321,0.907975,0.0004542446,0.0005002858,6.553909e-7,0.0004838294,0.07409831,0.001970587,0.0001193398,0.006585982,0.0004833264],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6647373,0.00005149371,0.3345942,0.000131162,0.0002238452,0.0001551176,0.00007574639,0.00002256414,0.000008577534],"genre_scores_gemma":[0.9971564,0.000001404728,0.00006410621,0.00001209685,0.00005496704,0.00250839,0.0001676174,0.00001118176,0.00002379447],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8065175,"threshold_uncertainty_score":0.9831375,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4383849550","doi":"10.2196/40433","title":"A Wearable Vibratory Device (The Emma Watch) to Address Action Tremor in Parkinson Disease: Pilot Feasibility Study","year":2023,"lang":"en","type":"article","venue":"JMIR Biomedical Engineering","topic":"Neurological disorders and treatments","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"","keywords":"Essential tremor; Physical medicine and rehabilitation; Handwriting; Parkinson's disease; Accelerometer; Medicine; Psychology; Computer science; Physical therapy; Artificial intelligence; Disease","retraction":null,"screen_n_in":null,"score":{"opus":0.06366858351246399,"gpt":0.3347170539844281,"spread":0.2710484704719641,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002299618,0.0001726544,0.0002470156,0.0001355432,0.00005554953,0.00001829561,0.0001169082,0.00005344878,0.00008310727],"category_scores_gemma":[0.0002285234,0.0001140965,0.00005970506,0.001071112,0.00003235872,0.00004950959,0.00008598532,0.000252272,0.0001567916],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009346346,"about_ca_system_score_gemma":0.00003681827,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000480813,"about_ca_topic_score_gemma":0.00001698321,"domain_scores_codex":[0.9985477,0.00004907366,0.0002390369,0.000392635,0.0004014746,0.000370073],"domain_scores_gemma":[0.9991425,0.000100653,0.00002116497,0.0003116057,0.00001880121,0.0004052364],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.006938535,0.03343858,0.7887713,0.001914523,0.0006085282,0.008180435,0.002615655,0.003909814,0.04596595,0.00004949945,0.01529386,0.09231326],"study_design_scores_gemma":[0.002197518,0.00119296,0.9799836,0.00008834463,0.00003513276,0.000002034894,0.0001371976,0.005561403,0.00005465937,0.00002049993,0.01060005,0.0001265789],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9936795,0.00007626115,0.00005547628,0.004058298,0.0001826859,0.0016408,0.00000831949,0.0002690943,0.00002955357],"genre_scores_gemma":[0.9986874,0.00001834955,0.00002628502,0.0004620263,0.00009717879,0.0005108804,0.0000173924,0.00002470188,0.0001557347],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1912123,"threshold_uncertainty_score":0.465272,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4390419498","doi":"10.2196/48497","title":"A Deep Learning Framework for Predicting Patient Decannulation on Extracorporeal Membrane Oxygenation Devices: Development and Model Analysis Study","year":2023,"lang":"en","type":"article","venue":"JMIR Biomedical Engineering","topic":"Mechanical Circulatory Support Devices","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"Irving Medical Center, Columbia University","keywords":"Extracorporeal membrane oxygenation; Deep learning; Medicine; Computer science; Artificial intelligence; Intensive care medicine; Biomedical engineering; Internal medicine","retraction":null,"screen_n_in":null,"score":{"opus":0.01660729729951807,"gpt":0.2550673375638606,"spread":0.2384600402643425,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004500918,0.0002556288,0.00032886,0.0006920459,0.0001222433,0.00005349471,0.0001162285,0.0001938887,0.00001246459],"category_scores_gemma":[0.000202365,0.0002570451,0.00008155592,0.001307572,0.00001131007,0.000120643,0.00004645793,0.0003049857,0.000007962422],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001180767,"about_ca_system_score_gemma":0.00001746422,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002143266,"about_ca_topic_score_gemma":0.000008940722,"domain_scores_codex":[0.9981026,0.0000182887,0.0005521519,0.0003878015,0.0005354618,0.0004036612],"domain_scores_gemma":[0.9991496,0.0003115382,0.00007268771,0.000165153,0.00004406879,0.000256957],"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":[0.000009579491,0.00005820057,0.003676774,0.0002324381,0.0003788899,0.000006854829,0.002107189,0.9766394,0.000428074,0.0002220679,0.000003519629,0.01623705],"study_design_scores_gemma":[0.0002715982,0.0001161723,0.02025184,0.00007271908,0.0001149404,8.074408e-7,0.0003673815,0.9779571,0.000195493,0.00005190796,0.0003366223,0.0002634257],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6134447,0.00002601845,0.385208,0.00001098796,0.0001068644,0.000473284,0.000003715507,0.0007158563,0.00001057768],"genre_scores_gemma":[0.984848,0.000002517151,0.01431221,0.00001541403,0.000081354,0.0005111307,0.0001626919,0.00006182139,0.000004841662],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3714033,"threshold_uncertainty_score":0.9999882,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4312112586","doi":"10.2196/42386","title":"Detection of Suicide Risk Using Vocal Characteristics: Systematic Review","year":2022,"lang":"en","type":"article","venue":"JMIR Biomedical Engineering","topic":"Voice and Speech Disorders","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"","keywords":"MEDLINE; Observational study; Randomized controlled trial; Poison control; Triage; Psychology; Medicine; Applied psychology; Psychiatry; Medical emergency; Surgery; Pathology","retraction":null,"screen_n_in":null,"score":{"opus":0.01028310850378507,"gpt":0.2655307262310337,"spread":0.2552476177272486,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000443832,0.0001176473,0.0005576268,0.0001671515,0.00005535824,0.000003536084,0.00008599344,0.00004812552,0.0001321334],"category_scores_gemma":[0.0005129316,0.0001042203,0.0001349873,0.0004239316,0.00002851982,0.00002936801,0.00006106132,0.0003248203,0.000006504117],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001112323,"about_ca_system_score_gemma":0.00004551646,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002780743,"about_ca_topic_score_gemma":3.254534e-7,"domain_scores_codex":[0.9986444,0.00004417634,0.0005014819,0.0001468806,0.0004718974,0.0001911942],"domain_scores_gemma":[0.9994072,0.00005888311,0.0001524119,0.0002206885,0.00003338087,0.0001274178],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00008565831,0.0005533393,0.0006438908,0.8050442,0.0004701919,0.0001976041,0.0003016938,0.0001913684,0.1870812,0.00002926218,0.0002230324,0.005178561],"study_design_scores_gemma":[0.006305413,0.00343062,0.01494814,0.3015971,0.006745008,0.002918983,0.001227198,0.6406012,0.007240719,0.00002792412,0.01308208,0.0018756],"study_design_candidate":"systematic_review","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.913074,0.02563161,0.05572961,0.0005375094,0.0009530585,0.003563021,0.0000935873,0.000355939,0.00006168263],"genre_scores_gemma":[0.9983804,0.0006573787,0.0003983441,0.000217871,0.00009047888,0.0001609453,0.00003331118,0.0000293194,0.00003197325],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6404098,"threshold_uncertainty_score":0.424998,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3025173173","doi":"10.2196/17106","title":"Challenges and Opportunities in Collecting and Modeling Ambulatory Electrodermal Activity Data","year":2020,"lang":"en","type":"article","venue":"JMIR Biomedical Engineering","topic":"Emotion and Mood Recognition","field":"Psychology","cited_by":9,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"National Institute of Environmental Health Sciences; National Institute on Drug Abuse; National Institutes of Health","keywords":"Ambulatory; Preprocessor; Anxiety; Computer science; Construct (python library); Artificial intelligence; Psychology; Medicine; Internal medicine; Psychiatry","retraction":null,"screen_n_in":null,"score":{"opus":0.2387499069014282,"gpt":0.3474284905200612,"spread":0.1086785836186329,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001823502,0.00009576709,0.0001389378,0.0001051658,0.0000261922,0.00001247115,0.00007158695,0.0001070541,0.00002613432],"category_scores_gemma":[0.00005368178,0.000100319,0.000009244852,0.00007261117,0.00002941673,0.0001146516,0.0001028812,0.0002411804,0.000002007783],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001075534,"about_ca_system_score_gemma":0.00001587393,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007898307,"about_ca_topic_score_gemma":0.000004664786,"domain_scores_codex":[0.9992723,0.00002984566,0.0001278276,0.0002838311,0.00009247397,0.0001937317],"domain_scores_gemma":[0.9996454,0.00005074366,0.00001917253,0.0001051543,0.000007866231,0.0001716797],"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":[0.0001357135,0.0002322579,0.00008650071,0.0006826582,0.0001255563,0.0001931037,0.01188229,0.0002081605,0.01633539,0.002393731,0.0005297365,0.9671949],"study_design_scores_gemma":[0.001095546,0.0001370659,0.004287753,0.00009483423,0.00001203296,0.00006692556,0.001165194,0.9886349,0.0000548996,0.00003093389,0.004170919,0.0002490164],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9811831,0.003445361,0.008386652,0.00514505,0.0001751139,0.0001971591,0.0000119483,0.000169011,0.001286662],"genre_scores_gemma":[0.9987218,0.0007004082,0.0001808846,0.0001753522,0.000157405,0.00001705502,0.00001868604,0.0000150414,0.00001337895],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9884267,"threshold_uncertainty_score":0.4090889,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4225884777","doi":"10.2196/34934","title":"Equity-Driven Sensing System for Measuring Skin Tone–Calibrated Peripheral Blood Oxygen Saturation (OptoBeat): Development, Design, and Evaluation Study","year":2022,"lang":"en","type":"article","venue":"JMIR Biomedical Engineering","topic":"Non-Invasive Vital Sign Monitoring","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"National Institute on Minority Health and Health Disparities; Division of Information and Intelligent Systems; National Institute of Allergy and Infectious Diseases; National Institute on Drug Abuse; National Institutes of Health; National Science Foundation","keywords":"Peripheral; Saturation (graph theory); Oxygen saturation; Computer science; Oxygen; Medicine; Internal medicine; Mathematics; Chemistry","retraction":null,"screen_n_in":null,"score":{"opus":0.03192052898680793,"gpt":0.2776065251905333,"spread":0.2456859962037254,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001219577,0.0003427006,0.0003384395,0.0003266475,0.0003556079,0.0001368247,0.0002019946,0.0001076952,0.0000134352],"category_scores_gemma":[0.00007928487,0.0003882661,0.00005752038,0.0005474042,0.00002139139,0.0002523912,0.0002514404,0.000329809,0.000001771853],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009039579,"about_ca_system_score_gemma":0.00009850741,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009054954,"about_ca_topic_score_gemma":0.000002045157,"domain_scores_codex":[0.9974626,0.0001186404,0.0005327117,0.0004290943,0.0009079577,0.0005489457],"domain_scores_gemma":[0.9992598,0.0001540597,0.00006613529,0.0002013459,0.0000887588,0.0002299053],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003871232,0.0001044189,0.0002145816,0.0005376476,0.0003243975,0.0000355677,0.002342024,0.2931184,0.6853729,0.00001542467,0.00004826718,0.01784765],"study_design_scores_gemma":[0.003006686,0.0003463437,0.002159596,0.0002124513,0.0001482306,0.00009078476,0.001550996,0.9110733,0.08002743,0.000006744822,0.0005933992,0.0007840886],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7131605,0.0002274173,0.2827612,0.0000124848,0.0009422989,0.002137699,0.000008078784,0.0007307375,0.00001960579],"genre_scores_gemma":[0.9770518,0.000001718437,0.02155796,0.000004557322,0.0003447949,0.0008665458,0.00005521621,0.0001111698,0.000006263683],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6179549,"threshold_uncertainty_score":0.9998569,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3128790666","doi":"10.2196/21105","title":"Monitoring of Sitting Postures With Sensor Networks in Controlled and Free-living Environments: Systematic Review","year":2021,"lang":"en","type":"article","venue":"JMIR Biomedical Engineering","topic":"Ergonomics and Musculoskeletal Disorders","field":"Psychology","cited_by":8,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"","keywords":"Sitting; Physical medicine and rehabilitation; Systematic review; Computer science; Human–computer interaction; Medicine; MEDLINE; Biology","retraction":null,"screen_n_in":null,"score":{"opus":0.003776192701581997,"gpt":0.2362927335596421,"spread":0.2325165408580601,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003118104,0.0001445806,0.0006251904,0.00007362671,0.00001603106,0.000009512598,0.000094537,0.00008919595,0.00002631901],"category_scores_gemma":[0.000287431,0.0001159996,0.00006452678,0.0001740036,0.00003703819,0.00003032994,0.00006864798,0.0001816648,0.000001270104],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002479653,"about_ca_system_score_gemma":0.000008755495,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001647814,"about_ca_topic_score_gemma":0.000001542307,"domain_scores_codex":[0.9988948,0.00006266199,0.0004536468,0.0002161075,0.0001372472,0.000235571],"domain_scores_gemma":[0.9992902,0.0002610752,0.0001042592,0.0002476884,0.000009745822,0.00008699229],"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":[0.0004999443,0.002650891,0.05448045,0.856027,0.00565281,0.001483848,0.00841145,0.01253504,0.04514189,0.002923402,0.000262365,0.009930897],"study_design_scores_gemma":[0.01619009,0.0005772302,0.3715501,0.5726208,0.0009417057,0.0002451337,0.006131717,0.02975434,0.0001119115,0.00001575444,0.0002654281,0.001595816],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8731576,0.1181474,0.006104945,0.0002848543,0.0004419498,0.001537303,0.000004984385,0.00005271805,0.0002682805],"genre_scores_gemma":[0.9971039,0.001712338,0.0007762533,0.00005974897,0.00006275748,0.000194471,0.000003332005,0.0000263745,0.0000608078],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3170696,"threshold_uncertainty_score":0.4730326,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3162675432","doi":"10.2196/26047","title":"A Simple Ventilator Designed To Be Used in Shortage Crises: Construction and Verification Testing","year":2021,"lang":"en","type":"article","venue":"JMIR Biomedical Engineering","topic":"Respiratory Support and Mechanisms","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"SLAC National Accelerator Laboratory; Office of Science; Stockholms Universitet; U.S. Department of Veterans Affairs; U.S. Department of Energy","keywords":"Economic shortage; Mechanical ventilator; Computer science; Laptop; Medicine; Mechanical ventilation; Anesthesia","retraction":null,"screen_n_in":null,"score":{"opus":0.03452610488303348,"gpt":0.2923791652418122,"spread":0.2578530603587787,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001527144,0.0001030672,0.0001944725,0.0001754378,0.00002349266,0.00001871481,0.00003058287,0.0001001662,0.0000715589],"category_scores_gemma":[0.0003566455,0.0001052426,0.00002654953,0.0005154393,0.00002175973,0.00005522727,0.00002798401,0.0001274512,0.000004297874],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005050191,"about_ca_system_score_gemma":0.0001031136,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004280248,"about_ca_topic_score_gemma":0.000001441871,"domain_scores_codex":[0.9991021,0.000009619691,0.0002401191,0.0002369051,0.0002079072,0.0002033262],"domain_scores_gemma":[0.9994637,0.00004580731,0.00002268895,0.0001453266,0.0000422695,0.0002802486],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00002118967,0.00006023751,0.00816463,0.0001540309,0.00001256664,0.0002334362,0.0002088174,0.00001876492,0.9789336,0.0001010973,0.000149133,0.01194254],"study_design_scores_gemma":[0.006693378,0.001437947,0.1956674,0.001191026,0.0001622075,0.0008743654,0.003053017,0.04169013,0.4884865,0.00008490156,0.2594816,0.001177521],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9712275,0.00005224377,0.02785788,0.0002847315,0.0001436395,0.0002939635,0.000004314271,0.00009070167,0.00004497316],"genre_scores_gemma":[0.9797214,0.000002830093,0.01974649,0.0002566155,0.0001076876,0.00007491884,0.00004134609,0.00002051369,0.00002815844],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.490447,"threshold_uncertainty_score":0.4291669,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3094446721","doi":"10.2196/24388","title":"Personalized Monitoring Model for Electrocardiogram Signals: Diagnostic Accuracy Study","year":2020,"lang":"en","type":"article","venue":"JMIR Biomedical Engineering","topic":"ECG Monitoring and Analysis","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"University of Leeds","keywords":"Computer science; Coronavirus disease 2019 (COVID-19); Personalized medicine; Artificial intelligence; Data mining; Machine learning; Medicine; Bioinformatics; Pathology","retraction":null,"screen_n_in":null,"score":{"opus":0.03406975684005058,"gpt":0.3234056578168371,"spread":0.2893359009767865,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000197206,0.0002407048,0.0005227198,0.0001546562,0.00007260303,0.00003752415,0.000146997,0.0001103727,0.00001170914],"category_scores_gemma":[0.002013849,0.0002144767,0.0003190553,0.0005851415,0.00002930298,0.00006578715,0.00004666805,0.0003218493,0.00001121766],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006881792,"about_ca_system_score_gemma":0.00006425359,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006014557,"about_ca_topic_score_gemma":5.755554e-8,"domain_scores_codex":[0.9982865,0.00001458186,0.0003430055,0.0003987531,0.0005050197,0.0004521678],"domain_scores_gemma":[0.9985497,0.0005510632,0.00004827441,0.0001869238,0.00007692139,0.0005871471],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00163624,0.006026051,0.1127901,0.005234944,0.008884172,0.001235819,0.02107207,0.1164332,0.5604653,0.0001062142,0.007086989,0.1590289],"study_design_scores_gemma":[0.002519758,0.0008602272,0.001738432,0.0001776342,0.0004509478,0.000008219236,0.0003712123,0.9895591,0.001260345,0.000005150607,0.002767732,0.0002813141],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5785105,0.0008223339,0.416439,0.001842688,0.0002440531,0.001425924,0.00001325255,0.0006851997,0.0000170464],"genre_scores_gemma":[0.9913574,0.00004849846,0.005920454,0.00008531987,0.001886926,0.000547432,0.00002168674,0.00005856117,0.00007368963],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8731258,"threshold_uncertainty_score":0.8746105,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4224935916","doi":"10.2196/36734","title":"A Novel Framework for Mixed Reality–Based Control of Collaborative Robot: Development Study","year":2022,"lang":"en","type":"article","venue":"JMIR Biomedical Engineering","topic":"Teleoperation and Haptic Systems","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"University of Wisconsin-Milwaukee","keywords":"Mixed reality; Augmented reality; Workspace; Robot; Human–computer interaction; Computer science; Teleoperation; Session (web analytics); Virtual reality; Artificial intelligence; World Wide Web","retraction":null,"screen_n_in":null,"score":{"opus":0.0155443279754069,"gpt":0.2612419955186875,"spread":0.2456976675432806,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003878977,0.0001674098,0.0003315354,0.0001823219,0.00008372184,0.00001714517,0.0001720841,0.00007041181,0.00006967675],"category_scores_gemma":[0.0001067579,0.0001719571,0.000052715,0.0005085936,0.0000185359,0.00002959881,0.00002330371,0.000186216,0.00000189823],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001524461,"about_ca_system_score_gemma":0.0001012543,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005810683,"about_ca_topic_score_gemma":0.000003320783,"domain_scores_codex":[0.9986753,0.00002188608,0.0004805353,0.000177974,0.0004029723,0.0002413631],"domain_scores_gemma":[0.9993547,0.0002349098,0.00004732065,0.0001751522,0.00006231812,0.0001256106],"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":[0.00006761689,0.0007569201,0.0000811771,0.0003852269,0.0003442687,0.000007329368,0.003607229,0.9536216,0.0345212,0.002548446,0.0007734453,0.00328553],"study_design_scores_gemma":[0.00362413,0.0003835159,0.002166546,0.00006795878,0.00002455079,0.000003893288,0.001627822,0.9319497,0.001552969,0.000006423956,0.05823784,0.0003546044],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02679607,0.00007715694,0.9704209,0.0001187213,0.0007970126,0.001352925,0.0001276431,0.0002852411,0.00002432569],"genre_scores_gemma":[0.9734811,2.359296e-7,0.02421492,0.0000314688,0.0000991523,0.002084278,0.00003764421,0.00003924396,0.00001192171],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9466851,"threshold_uncertainty_score":0.7012207,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4402547026","doi":"10.2196/58911","title":"Enhancing Ultrasound Image Quality Across Disease Domains: Application of Cycle-Consistent Generative Adversarial Network and Perceptual Loss","year":2024,"lang":"en","type":"article","venue":"JMIR Biomedical Engineering","topic":"Ultrasound Imaging and Elastography","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; University of California, Los Angeles; National Institutes of Health","keywords":"Preprint; Perception; Image (mathematics); Artificial intelligence; Quality (philosophy); Image quality; Computer science; Pattern recognition (psychology); Computer vision; Psychology; Physics; Neuroscience; World Wide Web","retraction":null,"screen_n_in":null,"score":{"opus":0.005749693740561004,"gpt":0.2833996621228106,"spread":0.2776499683822496,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004015604,0.0002072105,0.0003248461,0.00009959992,0.00008026755,0.00005251739,0.00006576014,0.0001019315,0.0000236964],"category_scores_gemma":[0.0002162644,0.000180224,0.0001593212,0.0004349647,0.000386595,0.0001137932,0.00004525014,0.0002920783,0.000008246433],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006446432,"about_ca_system_score_gemma":0.00006697568,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003166964,"about_ca_topic_score_gemma":0.000002925941,"domain_scores_codex":[0.9984168,0.00002950309,0.0004171367,0.0003923186,0.0003642268,0.0003799905],"domain_scores_gemma":[0.9989513,0.0003214729,0.00004453844,0.000223152,0.00004992287,0.0004095852],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0003582924,0.0003504466,0.008404983,0.00296927,0.0005573252,0.00007013816,0.006157721,0.0006931271,0.9705949,0.001471085,0.0004871636,0.00788551],"study_design_scores_gemma":[0.009886567,0.001148036,0.7312483,0.005590279,0.001377721,0.0009328704,0.00523925,0.1197925,0.007450703,0.001075988,0.1133306,0.002927266],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7690321,0.0008814756,0.2287249,0.0003515686,0.0003709542,0.0003244268,0.00007717383,0.0002085761,0.00002886465],"genre_scores_gemma":[0.98771,0.00007558394,0.01091951,0.00008186376,0.0009510675,0.00007836437,0.0001293279,0.00003293884,0.00002136359],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9631442,"threshold_uncertainty_score":0.7349324,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4295919728","doi":"10.2196/41327","title":"High-Dimensional Analysis of Finger Motion and Screening of Cervical Myelopathy With a Noncontact Sensor: Diagnostic Case-Control Study","year":2022,"lang":"en","type":"article","venue":"JMIR Biomedical Engineering","topic":"Cervical and Thoracic Myelopathy","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"Precursory Research for Embryonic Science and Technology","keywords":"Carpal tunnel syndrome; Medicine; Myelopathy; Motion (physics); Physical medicine and rehabilitation; Finger joint; Test (biology); Artificial intelligence; Sensitivity (control systems); Range of motion; Movement control; Surgery; Computer science; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.006393460922909383,"gpt":0.2333737999023161,"spread":0.2269803389794067,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004446147,0.0001846165,0.000738917,0.0005659509,0.00006573088,0.000005167201,0.0000632654,0.00006411634,0.0005324218],"category_scores_gemma":[0.0002017887,0.0001452219,0.0001234178,0.001297014,0.0000653284,0.00003520298,0.0001194999,0.0003361137,5.763351e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004338065,"about_ca_system_score_gemma":0.00003004847,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002045391,"about_ca_topic_score_gemma":0.00001186464,"domain_scores_codex":[0.9981654,0.00007131867,0.000484283,0.0003216508,0.0007222168,0.0002351047],"domain_scores_gemma":[0.9986855,0.0006429048,0.0001172785,0.0002210822,0.00007601824,0.0002572177],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.005273337,0.009483685,0.4540625,0.002424581,0.0165958,0.04154764,0.005910536,0.1459709,0.02117885,0.0002310345,0.00004158725,0.2972795],"study_design_scores_gemma":[0.00384918,0.00233592,0.7109702,0.00008303137,0.002967014,0.001186146,0.0005370248,0.2776965,0.00008935475,0.000001819593,0.0000706031,0.0002132624],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9810447,0.0001426576,0.01778514,0.0002720439,0.00005841467,0.0005187806,0.0001251769,0.00004740011,0.00000568141],"genre_scores_gemma":[0.9979717,0.000002536423,0.001725888,0.00005952283,0.00007151256,0.00008988097,0.00004745868,0.00002213418,0.000009433254],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2970662,"threshold_uncertainty_score":0.5921978,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3154086351","doi":"10.2196/15417","title":"Smartphone-Based Passive Sensing for Behavioral and Physical Monitoring in Free-Life Conditions: Technical Usability Study","year":2021,"lang":"en","type":"article","venue":"JMIR Biomedical Engineering","topic":"Digital Mental Health Interventions","field":"Psychology","cited_by":7,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"","keywords":"Usability; Human–computer interaction; Computer science; Psychology","retraction":null,"screen_n_in":null,"score":{"opus":0.03506814981134242,"gpt":0.4072241706456918,"spread":0.3721560208343493,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001824404,0.000156972,0.00027621,0.0001359087,0.00005101459,0.00003511107,0.00009946678,0.0001239416,0.0000288917],"category_scores_gemma":[0.0002887335,0.0001724571,0.00009710553,0.0003553754,0.0001173268,0.00009140408,0.00009697754,0.0002971439,0.000007389028],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001664494,"about_ca_system_score_gemma":0.00005892505,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005284106,"about_ca_topic_score_gemma":0.00001886179,"domain_scores_codex":[0.9985375,0.00005276789,0.0004148722,0.0004001415,0.0002096173,0.0003850893],"domain_scores_gemma":[0.998988,0.0003329549,0.00004299669,0.0003034107,0.00004554453,0.0002870819],"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":[0.001728368,0.1870122,0.1642986,0.006770557,0.001001921,0.005662307,0.01384637,0.0009349275,0.07659429,0.01383781,0.01271135,0.5156013],"study_design_scores_gemma":[0.01920631,0.005497104,0.9387382,0.002087602,0.0001798434,0.0002086189,0.006998759,0.01435746,0.005481603,0.0020931,0.003619803,0.001531604],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9934948,0.00008213239,0.003120569,0.0009762237,0.001276012,0.0007667982,0.000124816,0.0001321719,0.00002649688],"genre_scores_gemma":[0.9973614,1.807041e-7,0.001739227,0.00003263654,0.0002321554,0.0005312681,0.00004037681,0.00002696996,0.00003575555],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7744396,"threshold_uncertainty_score":0.7032596,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3201829940","doi":"10.2196/20652","title":"Tracking the Presence of Software as a Medical Device in US Food and Drug Administration Databases: Retrospective Data Analysis","year":2021,"lang":"en","type":"article","venue":"JMIR Biomedical Engineering","topic":"Pharmacovigilance and Adverse Drug Reactions","field":"Pharmacology, Toxicology and Pharmaceutics","cited_by":7,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"","keywords":"Food and drug administration; Tracking (education); Database; Drug; Software; Drug administration; Computer science; Medicine; Pharmacology; Psychology","retraction":null,"screen_n_in":null,"score":{"opus":0.08613789977954613,"gpt":0.4402550591798872,"spread":0.3541171594003411,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007903228,0.0001355877,0.0002620752,0.0001482214,0.000078126,0.00001475075,0.0003529179,0.0001292968,0.0003999149],"category_scores_gemma":[0.001438865,0.0001139478,0.00005347047,0.001160172,0.000171178,0.0002404159,0.0002632122,0.0007925548,0.000004244948],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003889972,"about_ca_system_score_gemma":0.0002672101,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003847791,"about_ca_topic_score_gemma":0.0002130889,"domain_scores_codex":[0.9985316,0.0001318504,0.0003404269,0.0003762583,0.0003652505,0.0002545965],"domain_scores_gemma":[0.9984798,0.0008078705,0.00007807564,0.0003523515,0.0000545541,0.0002273686],"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":[0.0009996152,0.007509741,0.6473255,0.002846585,0.01303885,0.005646362,0.01064777,0.01640363,0.1581403,0.008432241,0.01224515,0.1167642],"study_design_scores_gemma":[0.004748813,0.0001936279,0.1681098,0.0005007389,0.002072932,0.0004773011,0.00191277,0.4992873,0.04396643,0.0001309555,0.277622,0.0009773789],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9914655,0.001024242,0.003901151,0.002252884,0.000382991,0.0002517285,0.0005554589,0.00006718847,0.00009884495],"genre_scores_gemma":[0.9982368,0.0004483731,0.0003423877,0.0003796077,0.000144007,0.00003722335,0.0003760149,0.000009745654,0.00002580517],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4828837,"threshold_uncertainty_score":0.4646657,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3099109283","doi":"10.2196/18649","title":"Rhythmic Haptic Cueing for Gait Rehabilitation of People With Hemiparesis: Quantitative Gait Study","year":2020,"lang":"en","type":"article","venue":"JMIR Biomedical Engineering","topic":"Stroke Rehabilitation and Recovery","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"Manchester Metropolitan University","keywords":"Physical medicine and rehabilitation; Rhythm; Gait; Hemiparesis; STRIDE; Rehabilitation; Metronome; Psychology; Haptic technology; Computer science; Medicine; Simulation; Neuroscience","retraction":null,"screen_n_in":null,"score":{"opus":0.01334414916097209,"gpt":0.2778373670093836,"spread":0.2644932178484115,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001937576,0.0001611792,0.0004497077,0.0001909187,0.00002886861,0.000008348168,0.00006269479,0.00007688531,0.00003822424],"category_scores_gemma":[0.001402391,0.0001260045,0.0001308251,0.0005406608,0.00007035643,0.00007575165,0.00002165266,0.0001501012,0.000006841087],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005659035,"about_ca_system_score_gemma":0.00008129633,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008363959,"about_ca_topic_score_gemma":0.000001546992,"domain_scores_codex":[0.9986723,0.00002149565,0.0004141318,0.0002909496,0.0003866766,0.0002144112],"domain_scores_gemma":[0.9985045,0.0008812852,0.00008380058,0.0001492557,0.0001399726,0.0002412115],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.01395973,0.008154484,0.1585958,0.03790469,0.003574176,0.000182306,0.1813487,0.01333985,0.5560752,0.004263461,0.007553603,0.0150479],"study_design_scores_gemma":[0.02066991,0.04888876,0.4669433,0.002772393,0.0006099051,0.00005812359,0.04541978,0.403182,0.001830759,0.00005209077,0.00854367,0.001029392],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9521254,0.0001027831,0.04330768,0.002313015,0.0001088346,0.001878835,0.0000164072,0.0001194926,0.0000275464],"genre_scores_gemma":[0.9698495,0.000003239247,0.02947997,0.00008009683,0.0001274664,0.0003798353,0.0000228679,0.00003500462,0.0000220463],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5542445,"threshold_uncertainty_score":0.5138313,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3081320698","doi":"10.2196/20932","title":"Diagnosis of Type 2 Diabetes Using Electrogastrograms: Extraction and Genetic Algorithm–Based Selection of Informative Features","year":2020,"lang":"en","type":"article","venue":"JMIR Biomedical Engineering","topic":"Heart Rate Variability and Autonomic Control","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"","keywords":"Diabetes mellitus; Selection (genetic algorithm); Medicine; Correlation; Feature selection; Type 2 diabetes; Pattern recognition (psychology); Artificial intelligence; Computer science; Mathematics; Endocrinology","retraction":null,"screen_n_in":null,"score":{"opus":0.008815867461069172,"gpt":0.2516337893962416,"spread":0.2428179219351724,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007209439,0.00008887778,0.0002464888,0.00009377127,0.00001433618,0.000005307768,0.00002413989,0.00009086044,0.00003069914],"category_scores_gemma":[0.0001500282,0.00008102825,0.00004500503,0.0003362747,0.00004984623,0.00005421915,0.00001148964,0.0001620489,4.87951e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003501499,"about_ca_system_score_gemma":0.00008353435,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001142069,"about_ca_topic_score_gemma":1.33782e-7,"domain_scores_codex":[0.999354,0.00001280905,0.0002514119,0.00010386,0.0001305765,0.0001473092],"domain_scores_gemma":[0.9996024,0.00009162982,0.00005933755,0.00004903966,0.00005741258,0.0001401139],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005056954,0.0001819669,0.0080279,0.001034917,0.0001485094,0.0000036384,0.0003903741,0.002370291,0.8200607,0.000008213484,0.00004266805,0.1676803],"study_design_scores_gemma":[0.0007632413,0.0007536287,0.04383413,0.0001469109,0.00006650123,0.000007118938,0.00002846922,0.8754472,0.07684293,0.000001475234,0.002031444,0.00007701464],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.97852,0.0001648929,0.02052131,0.0004273836,0.00004523628,0.0002670262,0.000007044951,0.00004473441,0.000002328679],"genre_scores_gemma":[0.9724408,0.00001638672,0.02734239,0.00006757755,0.00009516906,0.00001693407,0.00001123099,0.00000885232,6.504536e-7],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8730769,"threshold_uncertainty_score":0.3304236,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4405281177","doi":"10.2196/57373","title":"Validation of a Wearable Sensor Prototype for Measuring Heart Rate to Prescribe Physical Activity: Cross-Sectional Exploratory Study","year":2024,"lang":"en","type":"article","venue":"JMIR Biomedical Engineering","topic":"Non-Invasive Vital Sign Monitoring","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"Fundação de Amparo à Pesquisa do Estado de São Paulo","keywords":"Cross-sectional study; Wearable computer; Physical activity; Exploratory research; Computer science; Medicine; Physical therapy; Embedded system","retraction":null,"screen_n_in":null,"score":{"opus":0.03519533078734916,"gpt":0.3006697711816955,"spread":0.2654744403943464,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004299913,0.0002544204,0.000297463,0.0003325453,0.00005136155,0.0001220409,0.0001439039,0.0001035271,0.00000914235],"category_scores_gemma":[0.0001573419,0.0002612963,0.0001285126,0.0006174563,0.00002893169,0.0003532566,0.00006518101,0.0002818511,0.00003255171],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001968807,"about_ca_system_score_gemma":0.00004794219,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004719614,"about_ca_topic_score_gemma":2.911372e-7,"domain_scores_codex":[0.9984724,0.00002508227,0.000277208,0.0003743537,0.0004501508,0.0004008017],"domain_scores_gemma":[0.9992405,0.0002266256,0.00001772147,0.0002115057,0.00008317963,0.0002204496],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00005252599,0.0001786548,0.0008930435,0.001043049,0.0001209123,0.00001182779,0.0005795122,0.046698,0.9495757,0.00001533908,0.00006359058,0.0007678985],"study_design_scores_gemma":[0.0008297022,0.0008714216,0.01618423,0.000620203,0.00003494176,0.00001190071,0.0001029101,0.1166697,0.861456,0.00003800558,0.002547939,0.0006331163],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9423407,0.00005463814,0.05363469,0.00002127649,0.001188112,0.001989497,0.00003128114,0.0007219713,0.00001786733],"genre_scores_gemma":[0.9957767,0.000001215738,0.0011712,0.000002407751,0.0009668693,0.001945853,0.000005126477,0.0001038787,0.0000267843],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08811966,"threshold_uncertainty_score":0.9999839,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4402223355","doi":"10.2196/60399","title":"Trends in South Korean Medical Device Development for Attention-Deficit/Hyperactivity Disorder and Autism Spectrum Disorder: Narrative Review","year":2024,"lang":"en","type":"review","venue":"JMIR Biomedical Engineering","topic":"Autism Spectrum Disorder Research","field":"Neuroscience","cited_by":7,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"","keywords":"Autism spectrum disorder; PsycINFO; Attention deficit hyperactivity disorder; Scopus; Narrative; Psychology; Government (linguistics); MEDLINE; Clinical psychology; Psychiatry; Autism; Medicine; Medical education; Political science","retraction":null,"screen_n_in":null,"score":{"opus":0.03525942073627519,"gpt":0.3603838288464226,"spread":0.3251244081101474,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0009918575,0.0009575338,0.002194068,0.00143869,0.0001917618,0.0001226419,0.0007886996,0.0006441828,0.0003050421],"category_scores_gemma":[0.0009429306,0.0007588749,0.0004700474,0.002912995,0.0002682713,0.0001835418,0.0006627367,0.001914027,0.0001045066],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003759041,"about_ca_system_score_gemma":0.0006606395,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002098051,"about_ca_topic_score_gemma":0.00006907261,"domain_scores_codex":[0.9940487,0.0002266287,0.001366545,0.001643112,0.001501272,0.001213703],"domain_scores_gemma":[0.9979898,0.000696371,0.0002194715,0.0004720209,0.000007025245,0.0006152536],"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":[0.000007631054,0.0003601961,0.0000240004,0.07760128,0.0001054775,0.0002107753,0.0004341016,0.000001082771,0.000004382534,0.003133695,0.0001516546,0.9179657],"study_design_scores_gemma":[0.0006644997,0.0001115997,0.0001580261,0.05382413,0.0001975284,0.0001627699,0.00003667602,0.002027106,6.261621e-7,0.00006105019,0.94172,0.001035953],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0004304181,0.9899283,0.001491935,0.004914491,0.0004452032,0.002309476,0.0001235354,0.0002892635,0.0000673957],"genre_scores_gemma":[0.001791026,0.994341,0.0002185145,0.00006407689,0.0001237731,0.002587443,0.0002444625,0.0002029479,0.0004267636],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9415684,"threshold_uncertainty_score":0.9994862,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4388263802","doi":"10.2196/47146","title":"Continuous Critical Respiratory Parameter Measurements Using a Single Low-Cost Relative Humidity Sensor: Evaluation Study","year":2023,"lang":"en","type":"article","venue":"JMIR Biomedical Engineering","topic":"Non-Invasive Vital Sign Monitoring","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":false},"ca_institutions":"École de Technologie Supérieure","funders":"Natural Sciences and Engineering Research Council of Canada; Institut de Recherche Robert-Sauvé en Santé et en Sécurité du Travail","keywords":"Exhalation; Respiratory rate; Respiratory monitoring; Ventilation (architecture); Simulation; Medicine; Wearable computer; Tidal volume; Computer science; Biomedical engineering; Respiratory system; Anesthesia; Heart rate; Engineering; Embedded system; Mechanical engineering; Internal medicine","retraction":null,"screen_n_in":null,"score":{"opus":0.1175759320375852,"gpt":0.3449102998219311,"spread":0.2273343677843458,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001265281,0.0003908055,0.0004139348,0.00051743,0.0001197311,0.00009399848,0.0002233555,0.0002415818,0.00005641173],"category_scores_gemma":[0.001726808,0.0004211996,0.0001181863,0.001201849,0.00009501779,0.0003759012,0.0001184231,0.0005248932,0.0001441372],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007394204,"about_ca_system_score_gemma":0.00004814638,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008482907,"about_ca_topic_score_gemma":0.000001500085,"domain_scores_codex":[0.9966122,0.0001355995,0.0005929177,0.0004773393,0.001397904,0.0007840544],"domain_scores_gemma":[0.9984781,0.0005346094,0.00004382703,0.0003851702,0.0001906606,0.0003676327],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001864306,0.0003908248,0.006506085,0.0003076796,0.0002527102,0.0002028587,0.0008650285,0.04292016,0.943458,0.000009845379,0.000357973,0.004710139],"study_design_scores_gemma":[0.006615297,0.001091753,0.04342869,0.001861694,0.0005536642,0.00004966146,0.00215995,0.7787544,0.1588289,0.0002206285,0.003070451,0.003364973],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.965232,0.0001045052,0.02951029,0.00001843346,0.002313912,0.001340176,0.00001929578,0.00134421,0.0001171778],"genre_scores_gemma":[0.9975084,0.000001349761,0.001354573,0.00001340883,0.0006491572,0.0003261941,0.00001658926,0.000124867,0.00000547042],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7846292,"threshold_uncertainty_score":0.999824,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4412974536","doi":"10.2196/72218","title":"Advancing Brain-Computer Interface Closed-Loop Systems for Neurorehabilitation: Systematic Review of AI and Machine Learning Innovations in Biomedical Engineering","year":2025,"lang":"en","type":"review","venue":"JMIR Biomedical Engineering","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":6,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"","keywords":"Neurorehabilitation; Preprint; Interface (matter); Computer science; Neural engineering; Brain–computer interface; Cognitive science; Artificial intelligence; Human–computer interaction; Engineering; Neuroscience; Psychology; Rehabilitation; Operating system; World Wide Web","retraction":null,"screen_n_in":null,"score":{"opus":0.01566603620715592,"gpt":0.315091819800127,"spread":0.2994257835929711,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001339639,0.0006801082,0.003044934,0.001454014,0.0000598702,0.00008987468,0.0006563232,0.000367446,0.00000684317],"category_scores_gemma":[0.007186764,0.0005647034,0.000342306,0.002313083,0.0001167147,0.0001823037,0.0003603232,0.001173145,0.000002712705],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001784183,"about_ca_system_score_gemma":0.0002037946,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005914446,"about_ca_topic_score_gemma":2.977597e-7,"domain_scores_codex":[0.9951974,0.0002771481,0.002501602,0.0008833134,0.0005436103,0.0005969942],"domain_scores_gemma":[0.9928046,0.005948227,0.0004998113,0.0004329518,0.000103638,0.0002107585],"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":[0.000002037372,0.00007148123,3.646234e-7,0.9802343,0.00004627611,0.00001416839,0.00007754617,0.000588612,0.0002038838,0.000430685,0.0003514909,0.01797918],"study_design_scores_gemma":[0.0002824812,0.000219026,4.451254e-7,0.683888,0.0001388128,0.0001012401,0.000005704484,0.1680411,0.00001901623,0.00000211525,0.1469055,0.0003965829],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0000281252,0.8678753,0.1262898,0.0004738162,0.001181507,0.003831441,0.0001051842,0.0002111701,0.000003664535],"genre_scores_gemma":[0.0004698718,0.9941412,0.002457194,0.000352641,0.0003189839,0.001873252,0.0001450122,0.0001333728,0.0001084686],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.2963462,"threshold_uncertainty_score":0.9996805,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3004454982","doi":"10.2196/17514","title":"Dementia-Related Products on an e-Commerce Platform","year":2020,"lang":"en","type":"article","venue":"JMIR Biomedical Engineering","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":6,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"","keywords":"Dementia; Product (mathematics); Neurocognitive; Internet privacy; Psychology; Business; Medicine; Psychiatry; Computer science; Cognition; Disease","retraction":null,"screen_n_in":null,"score":{"opus":0.04682282848274329,"gpt":0.3839721548993336,"spread":0.3371493264165903,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003860676,0.0001902611,0.000259771,0.0001102067,0.0003527839,0.000005697445,0.000252351,0.0002877782,0.0006067312],"category_scores_gemma":[0.0003088934,0.0001700229,0.00003533624,0.000659426,0.00003580332,0.00009837568,0.00007228191,0.001058455,0.00110398],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009338715,"about_ca_system_score_gemma":0.0002822858,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001971294,"about_ca_topic_score_gemma":0.000001507845,"domain_scores_codex":[0.9977216,0.0000535951,0.0006900712,0.0004256402,0.0003394671,0.0007696508],"domain_scores_gemma":[0.9979269,0.0001634209,0.0001150723,0.0003459941,0.00006005152,0.001388554],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006933209,0.002302904,0.00444221,0.01507306,0.0003432489,0.00008019266,0.01702309,0.001355244,0.03084282,0.1596323,0.3975274,0.3706842],"study_design_scores_gemma":[0.001112537,0.0003550362,0.006284102,0.0001417272,0.00001305054,0.000001510782,0.000166992,0.01804504,0.00004935909,0.00003925894,0.9735882,0.0002031371],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7011063,0.001036601,0.01943673,0.227366,0.005564873,0.02390854,0.0002201664,0.00642847,0.01493236],"genre_scores_gemma":[0.9770912,0.00007966975,0.001937859,0.01306759,0.001478446,0.005743967,0.0003161328,0.00008184502,0.0002033002],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5760608,"threshold_uncertainty_score":0.9996738,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4393111814","doi":"10.2196/56246","title":"Impact of Audio Data Compression on Feature Extraction for Vocal Biomarker Detection: Validation Study","year":2024,"lang":"en","type":"article","venue":"JMIR Biomedical Engineering","topic":"Voice and Speech Disorders","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"Glycemic Index Laboratories","funders":"","keywords":"Preprint; Speech recognition; Computer science; Compression (physics); Biomarker; Feature extraction; Artificial intelligence; Biology; World Wide Web","retraction":null,"screen_n_in":null,"score":{"opus":0.04402932370626702,"gpt":0.403566107535447,"spread":0.35953678382918,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002324713,0.000141957,0.0002065348,0.0002792645,0.00003087876,0.00002296864,0.00009909736,0.0001511776,0.00005057983],"category_scores_gemma":[0.000133976,0.0001032061,0.0001114575,0.000388659,0.00002188522,0.0001408189,0.00003924144,0.0002387934,0.00000859088],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008691908,"about_ca_system_score_gemma":0.00005589034,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001518401,"about_ca_topic_score_gemma":0.00000124066,"domain_scores_codex":[0.9989718,0.00001274583,0.0002042539,0.0003017485,0.0003411233,0.0001683234],"domain_scores_gemma":[0.9993504,0.0001200602,0.00002994661,0.00034092,0.00003608679,0.0001225653],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001131238,0.002198397,0.001107285,0.001522326,0.0009831798,0.0001002197,0.0003965149,0.0004631381,0.6127758,0.00001247761,0.03150075,0.3478087],"study_design_scores_gemma":[0.004877259,0.006175596,0.2214259,0.001575003,0.0004499172,0.0001547336,0.0002930361,0.6887122,0.009784464,0.00001235034,0.06607201,0.0004675877],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9258816,0.0003142664,0.07056747,0.0006312838,0.0008999804,0.001285678,0.00008503398,0.0002798783,0.00005485672],"genre_scores_gemma":[0.9986825,0.0000128749,0.0004350295,0.000009794453,0.0003172832,0.00005905304,0.0003595835,0.00002845171,0.00009544961],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6882491,"threshold_uncertainty_score":0.4208623,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}