{"meta":{"query_hash":"3e41bda3b746","filters":{"venue":"Telehealth and Medicine Today"},"cohort_total":10,"direct_labels_cover":0,"predictions_cover":10,"exported":10,"export_cap":100000,"truncated":false,"label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"permalink":"https://metacan.xera.ac/q/3e41bda3b746","api":"https://metacan.xera.ac/api/v1/cohort?venue=Telehealth+and+Medicine+Today"},"results":[{"id":"W2801098938","doi":"10.30953/tmt.v1.92","title":"WAME Editorial: Promoting Global Health: The World Association of Medical Editors Position on Editors’ Responsibility","year":2018,"lang":"en","type":"article","venue":"Telehealth and Medicine Today","topic":"Global Health and Surgery","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Grand Challenges Canada","keywords":"Publishing; Medical journal; Position statement; Statement (logic); Association (psychology); Global health; Position (finance); Political science; Social responsibility; Public relations; Medical research; Engineering ethics; Medicine; Psychology; Law; Health care; Family medicine; Business; Engineering","score_opus":0.01499258951481358,"score_gpt":0.3683215290650611,"score_spread":0.3533289395502475,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2801098938","genre_codex":"editorial","genre_gemma":"editorial","domain_codex":null,"domain_gemma":"evaluation","model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"editorial","genre_consensus":"editorial","domain_candidate":"evaluation","domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00006026262,0.00074370176,0.00017527131,0.06302684,0.93414694,0.00002581756,0.00003393214,0.00004924486,0.0017379321],"genre_scores_gemma":[0.0017675215,0.001492173,0.00036395158,0.03294924,0.9483224,0.000048790032,0.00003871723,0.00009406282,0.014923088],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9871567,0.0018766349,0.0013428632,0.0010623018,0.0075186878,0.0010428454],"domain_scores_gemma":[0.92973185,0.016244696,0.0057751643,0.001960648,0.037581287,0.008706436],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.014317267,0.0024141541,0.0023943002,0.0025896302,0.0046052006,0.012437471,0.004351665,0.01487015,0.022018543],"category_scores_gemma":[0.07710962,0.0008163906,0.0018347375,0.0014450152,0.0046472885,0.00485839,0.0022703833,0.01849787,0.02020396],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000022191978,0.000009610057,0.00004683141,0.000088320536,0.00000577308,0.000051267492,0.000022110416,0.000017946142,0.00005196228,0.0005235642,0.9956528,0.0035075864],"study_design_scores_gemma":[0.0000232031,0.00002254554,0.00035734486,0.00032820515,0.000016007627,0.00015940923,0.00009920691,0.00014961536,0.0001947463,0.000902918,0.9977223,0.000024538578],"about_ca_topic_score_codex":0.0015507813,"about_ca_topic_score_gemma":0.0038150176,"teacher_disagreement_score":0.9856827,"about_ca_system_score_codex":0.0034142064,"about_ca_system_score_gemma":0.007672911,"threshold_uncertainty_score":0.07571781},"labels":[],"label_agreement":null},{"id":"W3047721186","doi":"10.30953/tmt.v5.177","title":"Feasibility and Effectiveness of Mobile App for Active Case Finding for Tuberculosis in India","year":2020,"lang":"en","type":"article","venue":"Telehealth and Medicine Today","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Medicine; Tuberculosis; Slum; Case finding; Population; Mobile apps; Incidence (geometry); Pulmonary tuberculosis; Environmental health; Infectious disease (medical specialty); Pediatrics; Disease; Family medicine; Internal medicine; Pathology; World Wide Web","score_opus":0.06998263623175105,"score_gpt":0.45002986350995444,"score_spread":0.3800472272782034,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3047721186","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98696625,0.00053547893,0.0008164943,0.0017100498,0.000119566714,0.0028026819,0.00038840572,0.00015514411,0.0065060295],"genre_scores_gemma":[0.9866253,0.0010314063,0.007315311,0.00094362354,0.0001053248,0.002310714,0.0003057543,0.000024994464,0.0013375536],"study_design_codex":"design_other","study_design_gemma":"nonrandomized_trial","domain_scores_codex":[0.99302375,0.00397794,0.00063809945,0.00043187046,0.0012798633,0.00064848876],"domain_scores_gemma":[0.96738976,0.023836628,0.0020712996,0.0010664103,0.0038522696,0.0017835932],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009915228,0.00065839867,0.00045217405,0.0009994046,0.0009775916,0.0022998005,0.0015027542,0.00087970175,0.0036669436],"category_scores_gemma":[0.04074412,0.0003715007,0.0013514413,0.00043218402,0.0006848632,0.0018590974,0.001776526,0.0012238788,0.0010834205],"study_design_candidate":"nonrandomized_trial","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0085796155,0.037047025,0.34151846,0.0063010743,0.0003706023,0.0041176286,0.03220391,0.0012918217,0.0059850784,0.0010844959,0.012759402,0.54874086],"study_design_scores_gemma":[0.0034822477,0.13121173,0.7161155,0.0049115927,0.0027820095,0.005258263,0.06787872,0.017144615,0.0122065805,0.0015054189,0.036810994,0.00069236755],"about_ca_topic_score_codex":0.004708102,"about_ca_topic_score_gemma":0.0044873515,"teacher_disagreement_score":0.009915228,"about_ca_system_score_codex":0.0010609598,"about_ca_system_score_gemma":0.0025016228,"threshold_uncertainty_score":0.052437365},"labels":[],"label_agreement":null},{"id":"W4210525434","doi":"10.30953/tmt.v7.301","title":"Conducting a Global Quadruple Aim Thematic Analysis of Telemedicine Performance in Rural Indigenous Populations and Evidence-Based Recommendations for Improvement","year":2022,"lang":"en","type":"article","venue":"Telehealth and Medicine Today","topic":"Global Health Workforce Issues","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Indigenous; Telemedicine; Thematic map; Thematic analysis; Geography; Sociology; Qualitative research; Economic growth; Cartography; Social science; Health care; Biology; Economics","score_opus":0.17458115544880567,"score_gpt":0.4723682108249029,"score_spread":0.2977870553760972,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4210525434","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6650698,0.046602726,0.049973622,0.1541572,0.0026568826,0.021036923,0.0035268236,0.00023968906,0.056736257],"genre_scores_gemma":[0.8439229,0.022160493,0.10639029,0.009642663,0.00026045323,0.012970487,0.001486099,0.00012602529,0.0030406713],"study_design_codex":"qualitative","study_design_gemma":"qualitative","domain_scores_codex":[0.9479833,0.03693317,0.004253595,0.0014606924,0.0069157192,0.00245346],"domain_scores_gemma":[0.9019126,0.06138874,0.008183186,0.004075964,0.022046393,0.0023930778],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.1449477,0.0006109398,0.0012104558,0.007858744,0.0037221115,0.0055083567,0.0025704254,0.0011504616,0.0022090403],"category_scores_gemma":[0.11227927,0.00041601554,0.0020740072,0.0073719053,0.0047449614,0.0054309443,0.0071613854,0.002735766,0.00025464126],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002070712,0.0004784811,0.052450705,0.044001143,0.00096363976,0.00053449126,0.500896,0.0011951696,0.0016761518,0.040676117,0.018838976,0.33808213],"study_design_scores_gemma":[0.000058022335,0.00055686437,0.07597082,0.043785576,0.0007010473,0.00020262507,0.804894,0.0011871766,0.0012200398,0.012481739,0.058845382,0.00009677849],"about_ca_topic_score_codex":0.024191856,"about_ca_topic_score_gemma":0.049039733,"teacher_disagreement_score":0.1449477,"about_ca_system_score_codex":0.017613107,"about_ca_system_score_gemma":0.07009149,"threshold_uncertainty_score":0.7665658},"labels":[],"label_agreement":null},{"id":"W4386688730","doi":"10.30953/thmt.v8.429","title":"Sustainable Virtual Care in Ontario’s Health System: A Quality Metrics Comparison","year":2023,"lang":"en","type":"article","venue":"Telehealth and Medicine Today","topic":"Interprofessional Education and Collaboration","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto; Vector Institute","funders":"","keywords":"Quality (philosophy); Health care; Computer science; Business; Environmental economics; Nursing; Medicine; Economics; Economic growth","score_opus":0.06293481025036102,"score_gpt":0.4777736563346187,"score_spread":0.4148388460842577,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386688730","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9583224,0.0019707463,0.0017075056,0.004328078,0.000066298664,0.0006361374,0.004083129,0.00007127265,0.028814405],"genre_scores_gemma":[0.99714535,0.00031953224,0.0010118134,0.0001054545,0.000014225446,0.00008637114,0.00084899884,0.0000062277845,0.0004620566],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9925929,0.0015026723,0.0004133733,0.00031939748,0.0042735953,0.0008980319],"domain_scores_gemma":[0.983547,0.0018334261,0.004016581,0.0005356485,0.0072232606,0.0028441108],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0063623497,0.0002670267,0.00032585277,0.0031407916,0.0016590686,0.0030820651,0.0009134871,0.00041265393,0.0019202845],"category_scores_gemma":[0.016925272,0.00016326268,0.00053177465,0.0062085516,0.0015331556,0.0013517329,0.0026118625,0.00029124564,0.00012013464],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004198104,0.00021650235,0.9086792,0.0005443484,0.00025826233,0.000099108765,0.003664768,0.0038491816,0.0002886581,0.005029236,0.008276999,0.0686739],"study_design_scores_gemma":[0.00004106607,0.00030788334,0.98426473,0.00014000377,0.00005789438,0.000040862844,0.0036315983,0.003267577,0.00010825061,0.0003964937,0.007719549,0.000024021178],"about_ca_topic_score_codex":0.814555,"about_ca_topic_score_gemma":0.8430289,"teacher_disagreement_score":0.9494066,"about_ca_system_score_codex":0.050593406,"about_ca_system_score_gemma":0.037273236,"threshold_uncertainty_score":0.37307423},"labels":[],"label_agreement":null},{"id":"W4389042358","doi":"10.30953/thmt.v8.452","title":"Near-Term Digital Health Predictions: A Glimpse into Tomorrow’s AI-driven Healthcare","year":2023,"lang":"en","type":"article","venue":"Telehealth and Medicine Today","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Health care; Realm; Workflow; Workforce; Digital transformation; Patient safety; Digital health; Computer science; Risk analysis (engineering); Data science; Business; Political science","score_opus":0.01973898556809438,"score_gpt":0.3364375658625249,"score_spread":0.3166985802944305,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389042358","genre_codex":"commentary","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"commentary","genre_consensus":"commentary","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.017333612,0.17969301,0.041827135,0.5928175,0.0104263695,0.0001577876,0.0013521541,0.001426472,0.15496597],"genre_scores_gemma":[0.39220172,0.33211294,0.10437625,0.09853706,0.009201462,0.00031658306,0.003345594,0.00110913,0.058799267],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99879044,0.00042893592,0.00008974212,0.00014067237,0.00037032756,0.00017996253],"domain_scores_gemma":[0.9969559,0.0017435285,0.00009873048,0.00022592694,0.0004348755,0.0005410683],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0029971173,0.0009455393,0.00050166633,0.0021879715,0.0020568536,0.009778089,0.00168332,0.0043494464,0.012680891],"category_scores_gemma":[0.0069994293,0.0005676294,0.00089203997,0.0018562133,0.005323583,0.015606129,0.005971889,0.009150597,0.0028858727],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017861606,0.00017860532,0.0052652084,0.00088998885,0.00006945735,0.00092317746,0.005617936,0.0038916755,0.0010168452,0.44528744,0.20529181,0.33138928],"study_design_scores_gemma":[0.000015725329,0.0000747045,0.002098887,0.0022579534,0.000023009405,0.0005679396,0.0043631718,0.0054419395,0.0005456865,0.2318767,0.7526566,0.00007763469],"about_ca_topic_score_codex":0.015993899,"about_ca_topic_score_gemma":0.020015134,"teacher_disagreement_score":0.015993899,"about_ca_system_score_codex":0.0043409555,"about_ca_system_score_gemma":0.0050815023,"threshold_uncertainty_score":0.042421818},"labels":[],"label_agreement":null},{"id":"W4411910012","doi":"10.30953/thmt.v10.601","title":"Agentic AI and Ethics in Telemedicine","year":2025,"lang":"en","type":"article","venue":"Telehealth and Medicine Today","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Telemedicine; Engineering ethics; Psychology; Political science; Engineering; Health care; Law","score_opus":0.1387266919867815,"score_gpt":0.49241674882164327,"score_spread":0.35369005683486177,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411910012","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.017630048,0.025111446,0.15605582,0.41604182,0.0037967907,0.00018482254,0.00010000798,0.00016703519,0.38091224],"genre_scores_gemma":[0.8949677,0.009749716,0.029753678,0.033210445,0.004790359,0.00048641374,0.000056092227,0.00011085023,0.0268749],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.98075414,0.014743909,0.0007324382,0.0010255844,0.0019359988,0.00080792845],"domain_scores_gemma":[0.9657498,0.028010763,0.0015708535,0.0017686138,0.0016968608,0.0012031293],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.015388495,0.0004826682,0.00054000487,0.0013738117,0.00466509,0.010304589,0.0014010093,0.009171512,0.005239813],"category_scores_gemma":[0.024151962,0.00030675007,0.0006457834,0.0010237742,0.04143178,0.011059151,0.0047904635,0.0072189276,0.0008599681],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000005873751,0.000006865984,0.00012465085,0.000036679936,0.0000034061836,0.00004847712,0.0017166345,0.00053306966,0.000030373985,0.9915143,0.0023612718,0.0036183835],"study_design_scores_gemma":[0.000012220534,0.000015975407,0.00015367231,0.0002071997,0.0000030401388,0.00011597617,0.0012583692,0.0015549496,0.00007865216,0.9495193,0.04706598,0.000014654463],"about_ca_topic_score_codex":0.0029554162,"about_ca_topic_score_gemma":0.0013194147,"teacher_disagreement_score":0.015388495,"about_ca_system_score_codex":0.00802934,"about_ca_system_score_gemma":0.0054178503,"threshold_uncertainty_score":0.08138311},"labels":[],"label_agreement":null},{"id":"W4411910035","doi":"10.30953/thmt.v10.554","title":"Integrating Large Language Models into Clinical Decision Support Systems: A Novel Approach to UTI Diagnosis and Treatment","year":2025,"lang":"en","type":"article","venue":"Telehealth and Medicine Today","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Clinical decision support system; Decision support system; Computer science; Intensive care medicine; Medicine; Artificial intelligence","score_opus":0.04856991774644694,"score_gpt":0.4021485085357031,"score_spread":0.3535785907892562,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411910035","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0099709835,0.00054091436,0.968527,0.0029640282,0.00013116196,0.00048568606,0.0011299859,0.014350413,0.0018999219],"genre_scores_gemma":[0.11800582,0.00034358338,0.8762895,0.0010827815,0.000112336995,0.00036466398,0.0017151956,0.00042583357,0.001660288],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9955189,0.0017552254,0.0005051555,0.0011051671,0.00094832166,0.00016713447],"domain_scores_gemma":[0.9868422,0.008738947,0.00078367844,0.0013900448,0.0017213621,0.0005237673],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0056758844,0.0014614529,0.00088212546,0.0016637256,0.0010184956,0.0044523957,0.0028662088,0.0015994902,0.004416598],"category_scores_gemma":[0.023411606,0.00094885856,0.002457058,0.0012249512,0.0010625392,0.004269304,0.0037051276,0.003432477,0.0016617491],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010115234,0.0010811356,0.011911171,0.0012671893,0.0006100444,0.0013255887,0.003275878,0.27938113,0.018698,0.037692264,0.02885853,0.6148875],"study_design_scores_gemma":[0.000084520194,0.00011009034,0.0004978727,0.00009494626,0.00010381181,0.00017244602,0.0001627137,0.9431312,0.0046663224,0.034400415,0.016523683,0.000051932868],"about_ca_topic_score_codex":0.0122696515,"about_ca_topic_score_gemma":0.02127378,"teacher_disagreement_score":0.0122696515,"about_ca_system_score_codex":0.002128665,"about_ca_system_score_gemma":0.004329678,"threshold_uncertainty_score":0.030017316},"labels":[],"label_agreement":null},{"id":"W4414710214","doi":"10.30953/thmt.v10.582","title":"A Systematic Review of Internet of Things Technologies and Their Applications in The Early Detection And Management Of Diabetes Complications.","year":2025,"lang":"en","type":"article","venue":"Telehealth and Medicine Today","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"The Internet; Internet of Things; Randomized controlled trial; Mobile apps; Diabetes management; Clinical trial; MEDLINE; Diabetes mellitus","score_opus":0.047838288430712514,"score_gpt":0.4070514153424363,"score_spread":0.35921312691172375,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414710214","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0012248736,0.9957632,0.00025450505,0.00036321755,0.0002770034,0.000906803,0.0007266593,0.000010692533,0.00047307176],"genre_scores_gemma":[0.015036096,0.9801855,0.001291897,0.0008995604,0.00012897435,0.001675349,0.00044336414,0.000009162023,0.0003300199],"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","domain_scores_codex":[0.98776996,0.004056098,0.0048345802,0.0006502348,0.0024384886,0.00025054615],"domain_scores_gemma":[0.96669614,0.022572815,0.0062974873,0.0005416468,0.0034692762,0.0004226959],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0109166205,0.0015192667,0.0076051275,0.01508498,0.0009270616,0.002639075,0.0013172006,0.0016932995,0.005228891],"category_scores_gemma":[0.051492594,0.0009144041,0.007485032,0.014358859,0.0009799056,0.0023883746,0.0013893705,0.0011870175,0.00048673694],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027011134,0.000015120065,0.0005951416,0.96429837,0.008034286,0.00008717293,0.00014585581,0.000059682232,0.00017318146,0.00016403577,0.0015303163,0.02462663],"study_design_scores_gemma":[0.00038914272,0.0002726127,0.0035362458,0.8987774,0.07625033,0.00034479718,0.00021164365,0.000059260972,0.00020094415,0.00029810725,0.019625416,0.000034077573],"about_ca_topic_score_codex":0.008218745,"about_ca_topic_score_gemma":0.02994066,"teacher_disagreement_score":0.01508498,"about_ca_system_score_codex":0.003760755,"about_ca_system_score_gemma":0.017598486,"threshold_uncertainty_score":0.057733297},"labels":[],"label_agreement":null},{"id":"W4417521633","doi":"10.30953/thmt.v10.622","title":"AI Agents in Healthcare: The Need for Governance","year":2025,"lang":"","type":"article","venue":"Telehealth and Medicine Today","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba; McGill University","funders":"","keywords":"Corporate governance; Data governance; Order (exchange); Health care; Documentation; Clinical governance; Workforce; Workforce development","score_opus":0.11770288963427351,"score_gpt":0.46582868831389207,"score_spread":0.34812579867961857,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4417521633","genre_codex":"commentary","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"commentary","genre_consensus":"commentary","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011654101,0.013324664,0.39060402,0.45188317,0.0020690947,0.00032847255,0.00006730085,0.00037591223,0.12969333],"genre_scores_gemma":[0.77130526,0.014190522,0.15437274,0.036780167,0.0031685648,0.0010832285,0.00012909553,0.00034032582,0.018630134],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9723408,0.019408759,0.001121535,0.0021963993,0.003509023,0.0014234785],"domain_scores_gemma":[0.9646329,0.020741183,0.0022015218,0.0053020963,0.0035637098,0.003558529],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.04047713,0.00069893704,0.0011982694,0.0014875797,0.005109459,0.01763743,0.0022898035,0.00806647,0.0028198387],"category_scores_gemma":[0.033031195,0.0008604148,0.0007130678,0.0012911551,0.043187186,0.024043318,0.010622596,0.011210803,0.0010230833],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000005383596,0.0000116890415,0.0003082507,0.000054834967,0.000008958967,0.000042188385,0.0022592293,0.0009170645,0.00007778969,0.98523337,0.002898972,0.008182196],"study_design_scores_gemma":[0.000014792864,0.000019834268,0.00011676051,0.00021373953,0.000007588601,0.00006160291,0.0011814309,0.0015334557,0.000084452426,0.9312983,0.06545305,0.000014939486],"about_ca_topic_score_codex":0.0035440086,"about_ca_topic_score_gemma":0.0017568334,"teacher_disagreement_score":0.04047713,"about_ca_system_score_codex":0.005729725,"about_ca_system_score_gemma":0.013804431,"threshold_uncertainty_score":0.21406609},"labels":[],"label_agreement":null},{"id":"W7117885162","doi":"10.30953/thmt.v10.644","title":"Bringing Health Closer to People: The Case for Responsible Innovation","year":2025,"lang":"","type":"article","venue":"Telehealth and Medicine Today","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Health care; Healthcare system; Action (physics); Context (archaeology); Health data","score_opus":0.12582016468822937,"score_gpt":0.48294833225690215,"score_spread":0.35712816756867277,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7117885162","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009531651,0.0069909273,0.04518695,0.7691173,0.001486068,0.00019623376,0.000067845875,0.00018469033,0.16723832],"genre_scores_gemma":[0.8594253,0.006013569,0.02419652,0.09366463,0.002549273,0.0007788915,0.000059476897,0.00029730596,0.013015051],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9259155,0.045041475,0.0018494657,0.007917486,0.011991483,0.0072846008],"domain_scores_gemma":[0.8695956,0.087708175,0.0061110407,0.01862649,0.007703255,0.010255323],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.08343198,0.0013174252,0.0017014941,0.0030558011,0.011964863,0.0250404,0.0043378114,0.028437931,0.008807228],"category_scores_gemma":[0.084387854,0.0010361929,0.0017461102,0.001561347,0.10846817,0.038677122,0.01973596,0.021906845,0.0020849055],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019388839,0.000037093272,0.00025170582,0.00007106096,0.000017392247,0.00014373421,0.003152038,0.00030775357,0.00006694194,0.9860243,0.0051196837,0.0047887405],"study_design_scores_gemma":[0.0000484291,0.000022091326,0.00011459818,0.00022183279,0.0000096317135,0.00009450488,0.0014902469,0.00053331314,0.000094972886,0.95616156,0.041182823,0.000025967238],"about_ca_topic_score_codex":0.0051471945,"about_ca_topic_score_gemma":0.002642129,"teacher_disagreement_score":0.08343198,"about_ca_system_score_codex":0.014121909,"about_ca_system_score_gemma":0.026595695,"threshold_uncertainty_score":0.44123578},"labels":[],"label_agreement":null}]}